Msc ICT Innovation StuPO 2017 - tu-berlin.de · Um diesen Studiengangsbereich zu bestehen, müssen...

Studiengangsbeschreibung: keine Angabe

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Die Gewichtungsangabe '1.0' bedeutet, die Note wird nach dem Umfang in LP gewichtet (§ 47 Abs. 6 AllgStuPO); '0.0' bedeutet, die Notewird nicht gewichtet; jede andere Zahl ist ein Multiplikationsfaktor für den Umfang in LP. Weitere Hinweise zur Bildung der Gesamtnote sindder geltenden Studien- und Prüfungsordnung zu entnehmen.

Studiengang

Master of Science Double-Degree-Masterstudiengang ICT Innovation (MSc-ICT)

Abschluss:

Master of ScienceKürzel:

MSc-ICTImmatrikulation zum:

Wintersemester

Fakultät:

Fakultät IVVerantwortlich:

Küpper, Axel

Master of Science Double-Degree-Masterstudiengang ICT Innovation (MSc-ICT)

Msc ICT Innovation StuPO 2017

Datum:keine Angabe

Punkte:keine Angabe

27.08.2018 12:53 Uhr Double-Degree-Masterstudiengang ICT Innovation ... Seite 1 von 9

Innovation & Entrepreneurship Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Alle untergeordneten Studiengangsbereiche müssen bestanden werden.

Entry year Mandatory Unterbereich von Innovation & Entrepreneurship Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Alle Module dieses Studiengangsbereiches müssen bestanden werden. Module in diesem Studiengangsbereich:

Entry year Electives Unterbereich von Innovation & Entrepreneurship Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Es müssen mindestens 5 Leistungspunkte bestanden werden. Es dürfen höchstens 5 Leistungspunkte bestanden werden. Module in diesem Studiengangsbereich:

Exit year Mandatory Unterbereich von Innovation & Entrepreneurship Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Alle Module dieses Studiengangsbereiches müssen bestanden werden. Module in diesem Studiengangsbereich:

Studienrichtungen Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Es darf höchstens 1 Studiengangsbereich bestanden werden.

Major: Cloud Computing and Services Unterbereich von Studienrichtungen Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein:

Double-Degree-Masterstudiengang ICT Innovation (MSc) - Msc ICT Innovation StuPO 2017

Modulliste WS 2018/19

Titel LP Prüfungsform Benotet GewichtInnovation Management & Entrepreneurship Basics 6 Portfolioprüfung ja 1.0Venture Campus - ICT Innovation 9 Portfolioprüfung ja 1.0

Titel LP Prüfungsform Benotet GewichtDigital Innovation 6 Portfolioprüfung ja 1.0Innovation Economics 6 Portfolioprüfung ja 1.0Innovation Management - Corporate Innovation 6 Portfolioprüfung ja 1.0Innovation Marketing 6 Portfolioprüfung ja 1.0Innovation Policy 6 Portfolioprüfung ja 1.0Intellectual Property Management 6 Portfolioprüfung ja 1.0Open Source and IP in the Digital Society 6 Portfolioprüfung ja 1.0Standardisation and Plattform Management 6 Portfolioprüfung ja 1.0Strategic Innovation Management 6 Portfolioprüfung ja 1.0Strategic Management 6 Portfolioprüfung ja 1.0

Titel LP Prüfungsform Benotet GewichtI&E Study 6 Schriftliche Prüfung ja 1.0


Für diesen Studiengangsbereich sind keine Wahlregeln angegeben.

Entry year: Cloud Computing and Services Unterbereich von Major: Cloud Computing and Services Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Alle untergeordneten Studiengangsbereiche müssen bestanden werden.

Entry year Mandatory: Cloud Computing and Services Unterbereich von Entry year: Cloud Computing and Services Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Alle Module dieses Studiengangsbereiches müssen bestanden werden. Module in diesem Studiengangsbereich:

Entry year Electives: Cloud Computing and Services Unterbereich von Entry year: Cloud Computing and Services Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Es müssen mindestens 3 Leistungspunkte bestanden werden. Es dürfen höchstens 3 Leistungspunkte bestanden werden. Module in diesem Studiengangsbereich:

Entry year free choice: Cloud Computing and Services Unterbereich von Entry year: Cloud Computing and Services Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Es müssen mindestens 6 Leistungspunkte bestanden werden. Es dürfen höchstens 6 Leistungspunkte bestanden werden.

Titel LP Prüfungsform Benotet GewichtCloud Computing 6 Portfolioprüfung ja 1.0Distributed Algorithms 6 Schriftliche Prüfung ja 1.0Internet of Services Lab 9 Portfolioprüfung ja 1.0Network Architectures - Basics 6 Schriftliche Prüfung ja 1.0

Titel LP Prüfungsform Benotet Gewicht5G and IIoT Project 9 Portfolioprüfung ja 1.05G and IIoT Seminar 3 Portfolioprüfung ja 1.05th Generation Mobile Networks 6 Schriftliche Prüfung ja 1.0Advanced Information Management 1 (AIM-1) - Heterogeneous and DistributedInformation Systems (HDIS)

6 Portfolioprüfung ja 1.0

Advanced Information Management 3 (AIM-3) Scalable Data Science: Systems &Methods (SDSSM)


BDAPRO - Big Data Analytics Project 9 Portfolioprüfung ja 1.0Cloud Computing 6 Portfolioprüfung ja 1.0Cloud Prototyping 12 Portfolioprüfung ja 1.0DBT: Database Technology 6 Portfolioprüfung ja 1.0Digital Communities 6 Mündliche Prüfung ja 1.0Distributed Algorithms 6 Schriftliche Prüfung ja 1.0Enterprise Computing 6 Portfolioprüfung ja 1.0Hot Topics in Information Systems Engineering 3 Portfolioprüfung ja 1.0IDB-PRA: Implementation of a Database Engine (Database Technology Lab) 6 Portfolioprüfung ja 1.0IMPRO - Project Hot Topics in Information Management 6 Portfolioprüfung ja 1.0IMSEM - Seminar Hot Topics in Information Management 3 Portfolioprüfung ja 1.0Industrial Internet of Things (IIoT) 6 Schriftliche Prüfung ja 1.0Internet of Services Lab 9 Portfolioprüfung ja 1.0Mobile Services 6 Mündliche Prüfung ja 1.0Network Architectures - Basics 6 Schriftliche Prüfung ja 1.0Network Architectures - RouterLab 9 Portfolioprüfung ja 1.0Performance Evaluation of Computer Communication Systems 6 Portfolioprüfung ja 1.0


Exit year: Cloud Computing and Services Unterbereich von Major: Cloud Computing and Services Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Alle untergeordneten Studiengangsbereiche müssen bestanden werden.

Exit year Electives: Cloud Computing and Services Unterbereich von Exit year: Cloud Computing and Services Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Es müssen mindestens 18 Leistungspunkte bestanden werden. Es dürfen höchstens 18 Leistungspunkte bestanden werden. Module in diesem Studiengangsbereich:

Exit year free choice: Cloud Computing and Services Unterbereich von Exit year: Cloud Computing and Services Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Es müssen mindestens 6 Leistungspunkte bestanden werden. Es dürfen höchstens 6 Leistungspunkte bestanden werden.

Major: Data Science Unterbereich von Studienrichtungen Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Für diesen Studiengangsbereich sind keine Wahlregeln angegeben.

Exit year: Data Science Unterbereich von Major: Data Science Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Alle untergeordneten Studiengangsbereiche müssen bestanden werden.

Exit year Mandatory: Data Science Unterbereich von Exit year: Data Science

Titel LP Prüfungsform Benotet Gewicht5G and IIoT Project 9 Portfolioprüfung ja 1.05G and IIoT Seminar 3 Portfolioprüfung ja 1.05th Generation Mobile Networks 6 Schriftliche Prüfung ja 1.0Advanced Information Management 1 (AIM-1) - Heterogeneous and DistributedInformation Systems (HDIS)


Advanced Information Management 3 (AIM-3) Scalable Data Science: Systems &Methods (SDSSM)


BDAPRO - Big Data Analytics Project 9 Portfolioprüfung ja 1.0Cloud Computing 6 Portfolioprüfung ja 1.0Cloud Prototyping 12 Portfolioprüfung ja 1.0DBT: Database Technology 6 Portfolioprüfung ja 1.0Digital Communities 6 Mündliche Prüfung ja 1.0Distributed Algorithms 6 Schriftliche Prüfung ja 1.0Enterprise Computing 6 Portfolioprüfung ja 1.0Hot Topics in Information Systems Engineering 3 Portfolioprüfung ja 1.0IDB-PRA: Implementation of a Database Engine (Database Technology Lab) 6 Portfolioprüfung ja 1.0IMPRO - Project Hot Topics in Information Management 6 Portfolioprüfung ja 1.0IMSEM - Seminar Hot Topics in Information Management 3 Portfolioprüfung ja 1.0Industrial Internet of Things (IIoT) 6 Schriftliche Prüfung ja 1.0Internet of Services Lab 9 Portfolioprüfung ja 1.0Mobile Services 6 Mündliche Prüfung ja 1.0Network Architectures - Basics 6 Schriftliche Prüfung ja 1.0Network Architectures - RouterLab 9 Portfolioprüfung ja 1.0Performance Evaluation of Computer Communication Systems 6 Portfolioprüfung ja 1.0


Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Alle Module dieses Studiengangsbereiches müssen bestanden werden. Module in diesem Studiengangsbereich:

Exit year Electives: Data Science Unterbereich von Exit year: Data Science Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Es müssen mindestens 12 Leistungspunkte bestanden werden. Es dürfen höchstens 12 Leistungspunkte bestanden werden. Module in diesem Studiengangsbereich:

Exit year free chioce: Data Science Unterbereich von Exit year: Data Science Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Es müssen mindestens 6 Leistungspunkte bestanden werden. Es dürfen höchstens 6 Leistungspunkte bestanden werden.

Major: Embedded Systems Unterbereich von Studienrichtungen Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Für diesen Studiengangsbereich sind keine Wahlregeln angegeben.

Entry year: Embedded Systems Unterbereich von Major: Embedded Systems Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Alle untergeordneten Studiengangsbereiche müssen bestanden werden.

Entry year Mandatory: Embedded Systems Unterbereich von Entry year: Embedded Systems Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Alle Module dieses Studiengangsbereiches müssen bestanden werden. Module in diesem Studiengangsbereich:

Titel LP Prüfungsform Benotet GewichtAdvanced Information Management 3 (AIM-3) Scalable Data Science: Systems &Methods (SDSSM)


Titel LP Prüfungsform Benotet GewichtAdvanced Information Management 1 (AIM-1) - Heterogeneous and DistributedInformation Systems (HDIS)


Advanced Information Management 2 - Management of Data Streams 6 Mündliche Prüfung ja 1.0BDAPRO - Big Data Analytics Project 9 Portfolioprüfung ja 1.0BDASEM - Big Data Analytics Seminar 3 Portfolioprüfung ja 1.0Cloud Computing 6 Portfolioprüfung ja 1.0DBT: Database Technology 6 Portfolioprüfung ja 1.0IDB-PRA: Implementation of a Database Engine (Database Technology Lab) 6 Portfolioprüfung ja 1.0Machine Learning 1 6 Schriftliche Prüfung ja 1.0Speech Signal Processing and Speech Technology 6 Portfolioprüfung ja 1.0

Titel LP Prüfungsform Benotet GewichtAdvanced Computer Architecture 6 Portfolioprüfung ja 1.0Applied Embedded Systems Project 6 Portfolioprüfung ja 1.0Compiler Design 6 Portfolioprüfung ja 1.0Embedded Operating Systems 6 Mündliche Prüfung ja 1.0Quality Assurance of Embedded Systems 6 Mündliche Prüfung ja 1.0


Entry year free choice: Embedded Systems Unterbereich von Entry year: Embedded Systems Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Es müssen mindestens 6 Leistungspunkte bestanden werden. Es dürfen höchstens 6 Leistungspunkte bestanden werden.

Exit year: Embedded Systems Unterbereich von Major: Embedded Systems Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Alle untergeordneten Studiengangsbereiche müssen bestanden werden.

Exit year Electives: Embedded Systems Unterbereich von Exit year: Embedded Systems Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Es müssen mindestens 18 Leistungspunkte bestanden werden. Es dürfen höchstens 18 Leistungspunkte bestanden werden. Module in diesem Studiengangsbereich:

Exit year free choice: Embedded Systems Unterbereich von Exit year: Embedded Systems Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Es müssen mindestens 6 Leistungspunkte bestanden werden. Es dürfen höchstens 6 Leistungspunkte bestanden werden.

Major: Human Computer Interaction and Design Unterbereich von Studienrichtungen Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Für diesen Studiengangsbereich sind keine Wahlregeln angegeben.

Exit year: Human Computer Interaction and Design Unterbereich von Major: Human Computer Interaction and Design Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Alle untergeordneten Studiengangsbereiche müssen bestanden werden.

Exit year Mandatory: Human Computer Interaction and Design Unterbereich von Exit year: Human Computer Interaction and Design Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Alle Module dieses Studiengangsbereiches müssen bestanden werden.

Titel LP Prüfungsform Benotet GewichtAd-hoc and Sensor Networks 6 Portfolioprüfung ja 1.0Analysis and Optimization of Embedded Systems 6 Mündliche Prüfung ja 1.0Applications of Robotics and Autonomous Systems 9 Portfolioprüfung ja 1.0Cloud Computing 6 Portfolioprüfung ja 1.0Computer Arithmetic: Circuit Perspective 6 Portfolioprüfung ja 1.0Embedded Systems Security Lab 6 Portfolioprüfung ja 1.0Multicore Systems 6 Portfolioprüfung ja 1.0Networked Embedded Systems 6 Portfolioprüfung ja 1.0Project Hot Topics in Computer Vision A 9 Portfolioprüfung ja 1.0Project Hot Topics in Computer Vision B 9 Portfolioprüfung ja 1.0Recent Advances in Computer Architecture 3 Portfolioprüfung ja 1.0Seminar Software and Embedded Systems Engineering 3 Portfolioprüfung ja 1.0


Module in diesem Studiengangsbereich:

Exit year Electives: Human Computer Interaction and Design Unterbereich von Exit year: Human Computer Interaction and Design Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Es müssen mindestens 12 Leistungspunkte bestanden werden. Es dürfen höchstens 12 Leistungspunkte bestanden werden. Module in diesem Studiengangsbereich:

Exit year free choice: Human Computer Interaction and Design Unterbereich von Exit year: Human Computer Interaction and Design Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Es müssen mindestens 6 Leistungspunkte bestanden werden. Es dürfen höchstens 6 Leistungspunkte bestanden werden.

Major: Internet Technology and Architecture Unterbereich von Studienrichtungen Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Für diesen Studiengangsbereich sind keine Wahlregeln angegeben.

Entry year: Internet Technology and Architecture Unterbereich von Major: Internet Technology and Architecture Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Alle untergeordneten Studiengangsbereiche müssen bestanden werden.

Entry year Mandatory: Internet Technology and Architecture Unterbereich von Entry year: Internet Technology and Architecture Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Alle Module dieses Studiengangsbereiches müssen bestanden werden. Module in diesem Studiengangsbereich:

Titel LP Prüfungsform Benotet GewichtSpeech Signal Processing and Speech Technology 6 Portfolioprüfung ja 1.0

Titel LP Prüfungsform Benotet GewichtBiometric Identification 3 Portfolioprüfung ja 1.0Communication acoustics 6 Schriftliche Prüfung ja 1.0Computer Graphics Seminar A 3 Portfolioprüfung ja 1.0Computer-Supported Interaction 3 Schriftliche Prüfung ja 1.0Digital Image Processing 6 Schriftliche Prüfung ja 1.0Introduction to Physiological Computing 6 Portfolioprüfung ja 1.0Photogrammetric Computer Vision 6 Schriftliche Prüfung ja 1.0Projects in Machine Learning and Artificial Intelligence 9 Portfolioprüfung ja 1.0Study Project Quality & Usability (6 CP) 6 Portfolioprüfung ja 1.0Study Project Quality & Usability (9 CP) 9 Portfolioprüfung ja 1.0Usable Privacy 3 Portfolioprüfung ja 1.0

Titel LP Prüfungsform Benotet Gewicht5G and IIoT Seminar 3 Portfolioprüfung ja 1.05th Generation Mobile Networks 6 Schriftliche Prüfung ja 1.0Mobile Services 6 Mündliche Prüfung ja 1.0Network Architectures - Basics 6 Schriftliche Prüfung ja 1.0Network Technologies (Small) 6 Portfolioprüfung ja 1.0


Entry year Electives: Internet Technology and Architecture Unterbereich von Entry year: Internet Technology and Architecture Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Es müssen mindestens 3 Leistungspunkte bestanden werden. Es dürfen höchstens 3 Leistungspunkte bestanden werden. Module in diesem Studiengangsbereich:

Entry year free choice: Internet Technology and Architecture Unterbereich von Entry year: Internet Technology and Architecture Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Es müssen mindestens 6 Leistungspunkte bestanden werden. Es dürfen höchstens 6 Leistungspunkte bestanden werden.

Exit year: Internet Technology and Architecture Unterbereich von Major: Internet Technology and Architecture Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Alle untergeordneten Studiengangsbereiche müssen bestanden werden.

Exit year Electives: Internet Technology and Architecture Unterbereich von Exit year: Internet Technology and Architecture Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Es müssen mindestens 18 Leistungspunkte bestanden werden. Es dürfen höchstens 18 Leistungspunkte bestanden werden. Module in diesem Studiengangsbereich:

Titel LP Prüfungsform Benotet Gewicht5G and IIoT Project 9 Portfolioprüfung ja 1.0Ad-hoc and Sensor Networks 6 Portfolioprüfung ja 1.0Advanced Algorithmics 9 Schriftliche Prüfung ja 1.0DBT: Database Technology 6 Portfolioprüfung ja 1.0Digital Communities 6 Mündliche Prüfung ja 1.0Embedded Operating Systems 6 Mündliche Prüfung ja 1.0High-speed Network Technologies with Lab 6 Portfolioprüfung ja 1.0IDB-PRA: Implementation of a Database Engine (Database Technology Lab) 6 Portfolioprüfung ja 1.0Industrial Internet of Things (IIoT) 6 Schriftliche Prüfung ja 1.0Master Seminar: Operating Complex IT Systems 3 Portfolioprüfung ja 1.0Network Architectures - Master Project 12 Portfolioprüfung ja 1.0Network Architectures - Master Project (small) 6 Portfolioprüfung ja 1.0Network Architectures - RouterLab 9 Portfolioprüfung ja 1.0Network Architectures - Seminar 3 Portfolioprüfung ja 1.0Network Architectures Specialization (big) 9 Mündliche Prüfung ja 1.0Network Architectures Specialization (small) 6 Mündliche Prüfung ja 1.0Network Technologies (Medium) 9 Portfolioprüfung ja 1.0Network Technologies (Small) 6 Portfolioprüfung ja 1.0Network protocol programming lab 6 Portfolioprüfung ja 1.0Networked Embedded Systems 6 Portfolioprüfung ja 1.0Parameterized Algorithmics 6 Mündliche Prüfung ja 1.0Performance Evaluation of Computer Communication Systems 6 Portfolioprüfung ja 1.0Project in advanced network technologies 6 Portfolioprüfung ja 1.0Special Topics in Communications Networks and Autonomous Security 3 Portfolioprüfung ja 1.0


Exit year free choice: Internet Technology and Architecture Unterbereich von Exit year: Internet Technology and Architecture Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Es müssen mindestens 6 Leistungspunkte bestanden werden. Es dürfen höchstens 6 Leistungspunkte bestanden werden.

Masterarbeit Um diesen Studiengangsbereich zu bestehen, müssen die folgenden Bedingungen erfüllt sein: Für diesen Studiengangsbereich sind keine Wahlregeln angegeben. Module in diesem Studiengangsbereich:

Titel LP Prüfungsform Benotet Gewicht5G and IIoT Project 9 Portfolioprüfung ja 1.0Ad-hoc and Sensor Networks 6 Portfolioprüfung ja 1.0Advanced Algorithmics 9 Schriftliche Prüfung ja 1.0DBT: Database Technology 6 Portfolioprüfung ja 1.0Digital Communities 6 Mündliche Prüfung ja 1.0Embedded Operating Systems 6 Mündliche Prüfung ja 1.0High-speed Network Technologies with Lab 6 Portfolioprüfung ja 1.0IDB-PRA: Implementation of a Database Engine (Database Technology Lab) 6 Portfolioprüfung ja 1.0Industrial Internet of Things (IIoT) 6 Schriftliche Prüfung ja 1.0Master Seminar: Operating Complex IT Systems 3 Portfolioprüfung ja 1.0Network Architectures - Master Project 12 Portfolioprüfung ja 1.0Network Architectures - Master Project (small) 6 Portfolioprüfung ja 1.0Network Architectures - RouterLab 9 Portfolioprüfung ja 1.0Network Architectures - Seminar 3 Portfolioprüfung ja 1.0Network Architectures Specialization (big) 9 Mündliche Prüfung ja 1.0Network Architectures Specialization (small) 6 Mündliche Prüfung ja 1.0Network Technologies (Medium) 9 Portfolioprüfung ja 1.0Network Technologies (Small) 6 Portfolioprüfung ja 1.0Network protocol programming lab 6 Portfolioprüfung ja 1.0Networked Embedded Systems 6 Portfolioprüfung ja 1.0Parameterized Algorithmics 6 Mündliche Prüfung ja 1.0Performance Evaluation of Computer Communication Systems 6 Portfolioprüfung ja 1.0Project in advanced network technologies 6 Portfolioprüfung ja 1.0Special Topics in Communications Networks and Autonomous Security 3 Portfolioprüfung ja 1.0

Titel LP Prüfungsform Benotet GewichtMasterarbeit ICT Innovation StuPO 2016 30 Abschlussarbeit ja 1.0


Learning Outcomes In this seminar you will learn the comprehensive preparation and presentation of a research topic in English. To achieve this you will have toread and categorize a scientific English text, conduct background research and present your findings.

Requirements for participation and examination Desirable prerequisites for participation in the courses: This course is aimed at master students with a focus on database systems and information management and should be chosen after the2nd master semester. To be able to participate you should have successfully completed 'Database Technology DBT' and one of the'Advanced Information Management AIM' (1,2,3) courses.This seminar can be taken very well by students who are directly in front of their master thesis or have already completed it and areinterested in a doctorate in information management.It is vital that you have a sound understanding of written and spoken English.

Mandatory requirements for the module test application: No information

Module completion

IMSEM - Seminar Hot Topics in Information Management

Module title:

IMSEM - Seminar Hot Topics in Information Management

Credits:

3

Responsible person:

Markl, Volker

Office:

EN 7

Contact person:

Rabl, Tilmann

Website:

http://www.dima.tu-berlin.de

Display language:

Englisch

E-mail address:

[email protected]

Grading: Type of exam: Language:graded Portfolio examination

100 points in totalEnglish

Grading scale:Note: 1.0 1.3 1.7 2.0 2.3 2.7 3.0 3.3 3.7 4.0Punkte: 95.0 90.0 85.0 80.0 75.0 70.0 65.0 60.0 55.0 50.0

Test description:The exam will be done as a 'portfolio examination', including two deliverable assessments, totaling for 100 portfolio points:- seminar presentation (50 portfolio points)- written seminar report (50 portfolio points)

The final grade according to § 47 (2) AllgStuPO will be calculated with the faculty grading table 2.(Die Gesamtnote gemäß § 47 (2) AllgStuPO wird nach dem Notenschlüssel 2 der Fakultät IV ermittelt.)

Test elements Categorie Points Duration/Extent(Deliverable assessment) Written Seminar Report written 50 approx. 20 pages(Deliverable assessment) Seminar Presentation oral 50 60 min.

27.08.2018 12:53 Uhr Modulbeschreibung #40001/4 Seite 1 von 1

Learning Outcomes Students who have completed this module can design and analyze algorithms for computational problems arising in various applicationcontexts. When facing a concrete computational problem, they are able to choose, from a wide range of advanced techniques, a strategy toefficiently solve the problem.This includes strategies for solving problems that are computationally hard in the worst case. In particular, the students know about currentresearch topics in algorithmics.

Requirements for participation and examination Desirable prerequisites for participation in the courses: a) obligatory: basic knowledge on algorithm designb) desirable: basic understanding of P vs. NP classification


Module completion

Advanced Algorithmics

Module title:

Advanced Algorithmics

Credits:

9

Responsible person:

Niedermeier, Rolf

Office:

TEL 5-1

Contact person:

Niedermeier, Rolf

Website:

http://www.akt.tu-berlin.de/menue/teaching/

Display language:

Englisch

E-mail address:

[email protected]

Grading: Type of exam: Language: Duration/Extent:graded Written exam English 90 min


Learning Outcomes Successful participants of this module have knowledge about recent research results and trends in the domain of operating complex ITsystems. Through the work in this seminar the participant will gain methodological skills in preparing literature of current research topics, thescientific work and the presentation.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Basic knowledge of the modules "Distributed Systems" is assumed.


Module completion

Master Seminar: Operating Complex IT Systems

Module title:

Master Seminar: Operating Complex IT Systems

Credits:

3

Responsible person:

Kao, Odej

Office:

EN 59

Contact person:

No information

Website:

http://www.cit.tu-berlin.de

Display language:

Englisch

E-mail address:

[email protected]


100 points in totalGerman/English


Test description:No information

Test elements Categorie Points Duration/ExtentPaper written 45 5-6 pages IEEE StylePresentation oral 55 20 minutes + 5-10 minutes

discussion


Learning Outcomes The global data volume is increasing dramatically each year. Understanding how to store, process and manage these huge amounts of dataefficiently is a key requirement for software engineers and data analysts in the modern IT world. This lab (following the correspondinglecture topics of DBT-Database Technology) will teach students both the fundamentals of data processing in traditional single-nodedatabase systems and how to scale out these techniques to huge amounts of data in large-scale, distributed environments.During the implementation part of the lab, students will get hands-on experience with important data processing techniques by implementingseveral components of a relational database system and by using parallel programming platforms like Apache Hadoop or Nephele/PACT.

Requirements for participation and examination Desirable prerequisites for participation in the courses: This course is the base course for master students with focus on database systems and information management and should be attendedin the first semester of the master program. In contrast to the introduction of database systems (MPGI5/DBS), which looks databasesystems from an application programmers point of view, this class focuses on the internals of database systems.To participate, students are required to have successfully completed a Bachelor in computer science with a focus on database systems(participation in the Datenbankpraktikum, Datenbankprojekt). As a mandatory requirement, knowledge of data modeling, relational algebra, and SQL as well as a very good (!!) command of Javaprogramming and the GIT version control system are essential to participate in the course. These topics will not be repeated in the lecture.


Module completion

IDB-PRA: Implementation of a Database Engine (Database Technology Lab)

Module title:

IDB-PRA: Implementation of a Database Engine (Database Technology Lab)

Credits:

6

Responsible person:

Markl, Volker

Office:

EN 7

Contact person:

Traub, Jonas

Website:


Display language:

Englisch

E-mail address:

[email protected]




Test description:The final grade according to § 47 (2) AllgStuPO will be calculated with the faculty grading table 2.(Die Gesamtnote gemäß § 47 (2) AllgStuPO wird nach dem Notenschlüssel 2 der Fakultät IV ermittelt.)

Test elements Categorie Points Duration/ExtentDeliverable assessment: Implementation of databasemodules for IO handling (3 tasks with 10 points each)

practical 30 36h (12h/task)

Deliverable assessment: Implementation of a databaseindex (1 tasks with 10 points)

practical 10 12h

Deliverable assessment: Implementation of databaseoperators (3 tasks with 25 points in total)


Deliverable assessment: Implementation of databaseoptimizer components (2 tasks with 25 points in total)


Deliverable assessment: Implementation of databasecomponents for massively parallel processing (1 task with 10points)

practical 10 12h


Learning Outcomes Project title: "Scientific Process in Computer Vision: From Ideas to Publications" Participants will gain significant insights into computer vision related problems and solutions. The goal is not to explore the whole field ofresearch completely, but rather to confront the participants with the full complexity of one specific problem and to challenge their owninitiative. Therefore we do not provide a pedagogically gentle introduction of the learners to the scientific area, but we allow insights andparticipation in research and development. The ability of the participants to work in a team shall be improved by this module.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Knowledge from the modules "Digital Image Processing" or "Automatic Image Analysis" or "Photogrammetric Computer Vision". Fluent inspoken and written English, programming and math skills


Module completion

Project Hot Topics in Computer Vision A

Module title:

Project Hot Topics in Computer Vision A

Credits:

9

Responsible person:

Hellwich, Olaf

Office:

MAR 6-5

Contact person:

Ley, Andreas

Website:

http://www.cv.tu-berlin.de

Display language:

Englisch

E-mail address:

[email protected]





Test elements Categorie Points Duration/ExtentPresentation Part II oral 10 No informationPresentation Part III oral 10 No informationSoftware practical 40 No informationSummary Part I written 5 No informationWritten report Part II written 10 No informationWritten report Part IV written 25 No information


Lernergebnisse Die Teilnehmer gewinnen signifikante Einblicke in Computer Vision bezogene Probleme und Lösungen. Das Ziel besteht nicht darin dengesamten Bereich der Wissenschaft komplett zu erforschen, sondern die Teilnehmer mit der vollen Komplexität eines spezifischenProblems zu konfrontieren und ihre Eigeninitiative herauszufordern. Wir bieten Einblicke und Teilnahme an Forschung und Entwicklung. DieFähigkeit der Teilnehmer in einem Team zu arbeiten wird durch dieses Modul verbessert.

Voraussetzungen für die Teilnahme / Prüfung Wünschenswerte Voraussetzungen für die Teilnahme an den Lehrveranstaltungen: keine

Verpflichtende Voraussetzungen für die Modulprüfungsanmeldung: Keine Angabe

Abschluss des Moduls

Project Hot Topics in Computer Vision B

Titel des Moduls:

Project Hot Topics in Computer Vision B

Leistungspunkte:

9

Verantwortliche Person:

Hellwich, Olaf

Sekretariat:

MAR 6-5

Ansprechpartner:

Dennert, Marion

Webseite:

http://www.cv.tu-berlin.de

Anzeigesprache:

Deutsch/Englisch

E-Mailadresse:

[email protected]

Benotung: Prüfungsform: Sprache:benotet Portfolioprüfung

100 Punkte insgesamtDeutsch/Englisch

Notenschlüssel:Note: 1.0 1.3 1.7 2.0 2.3 2.7 3.0 3.3 3.7 4.0Punkte: 86.0 82.0 78.0 74.0 70.0 66.0 62.0 58.0 54.0 50.0

Prüfungsbeschreibung:Keine Angabe

Prüfungselemente Kategorie Punkte Dauer/UmfangDokumentation (Ergebnisprüfung) schriftlich 35 Keine AngabePräsentation (Ergebnisprüfung) mündlich 20 2 x 15 MinutenSoftware (Ergebnisprüfung) praktisch 40 Keine AngabeZusammenfassung (Ergebnisprüfung) schriftlich 5 Keine Angabe


Learning Outcomes Students acquire a deep understanding of fundamental distributed systems concepts and their application in modern enterprise, web, andcloud architectures. They are able to put theoretical insights into practice, i.e., implement working prototypes and experimentally evaluatethem. After completing this course, students will be able to reason about complex technological choices in the field of enterprise computing.Furthermore, they learn to clearly communicate insights and findings and engage in discussion.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Advanced programming skills in Java and knowledge of fundamental distributed systems and middleware concepts are required tounderstand lecture contents. Knowledge of Web-technology fundamentals and service-oriented architectures (REST and SOAP/WSDL) ishighly recommended.


Module completion

Enterprise Computing

Module title:

Enterprise Computing

Credits:

6

Responsible person:

Tai, Stefan

Office:

EN 14

Contact person:

Hummel, Anita

Website:

http://www.ise.tu-berlin.de

Display language:

Englisch

E-mail address:

No information



Grading scale:This exam uses its own grading scale (see test description)..

Test description:In total, 100 portfolio points can be achieved.

In accordance to §47 (2) AllgStuPO, the overall grade is based on following grading scale:

1.0 at [91,5;100]1.3 at [88;91,5)1.7 at [84,5;88)2.0 at [81;84,5)2.3 at [77,5;81)2.7 at [74;77,5)3.0 at [70,5;74)3.3 at [67;70,5)3.7 at [63,5;67)4.0 at [60;63,5)5.0 at [0;60)

Test elements Categorie Points Duration/Extent(Punktuelle Leistungsabfrage) Written Test written 70 70 Min.(Ergebnisprüfung) Assignment practical 30 ca. 40h


Learning Outcomes Participants have knowledge on current research developments in the field of information systems engineering. They deepen theirunderstanding of research and common scientic practices in general, e.g. in the contexts of Cloud Computing, IoT, Blockchains,Microservices, Privacy Engineering and other.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Knowledge on Java, Distributed Systems, and Middleware concepts is required. We expect our students to be willing to work with newtechnologies, systems, and concepts - this also includes LaTeX.


Module completion

Hot Topics in Information Systems Engineering

Module title:

Hot Topics in Information Systems Engineering

Credits:

3

Responsible person:

Tai, Stefan

Office:

EN 14

Contact person:

Tai, Stefan

Website:


Display language:

Englisch

E-mail address:

[email protected]




Test description:The final marks will comprise a seminar thesis and the presentation of its results. The seminar includes a peer-review phase wherestudents are asked to review theses of other students. The quality of said review is also considered.

Insgesamt können 100 Portfoliopunkte erreicht werden, die Gesamtnote gemäß §47 (2) AllgStuPO wird nach dem Notenschlüssel 2 derFakultät IV ermittelt.

Test elements Categorie Points Duration/Extent(Ergebnisprüfung) Kurzreview anderer Seminarabgaben written 10 2 h(Ergebnisprüfung) Schriftliche Ausarbeitung written 60 70 h(Ergebnisprüfung) Präsentation practical 30 1 h


Learning Outcomes Students gain/are expected to- Knowledge on the topic of privacy with focus on human aspects in information privacy- Conduct research in a group- Give a presentation on a specific topic to an audience- Participate in a one-day workshop

Requirements for participation and examination Desirable prerequisites for participation in the courses: Basic knowledge in information and communication technologies and HCI is recommended.


Module completion

Usable Privacy

Module title:

Usable Privacy

Credits:

3

Responsible person:

Möller, Sebastian

Office:

TEL 18

Contact person:

Hirsch, Tobias

Website:

http://www.qu.tu-berlin.de/menue/studium_und_lehre/

Display language:

Englisch

E-mail address:

[email protected]




Test description:

Tests: On three specific dates there is a short test around the topics dealt with during the seminar.

Presentation: Based on a given or self-chosen topic the students hold presentations in small groups.

Written assignment: The students plan and conduct in groups a small study related to privacy and present the study including the results ina short report.

Test elements Categorie Points Duration/Extent(Examination) 3 tests each 4 points written 12 30 min(Deliverable assessment) Presentation oral 28 15-30 min(Deliverable assessment) Written assignment written 60 3-5 pages per group


Learning Outcomes Students gain- Understanding of the most important principles of human-computer interaction.- Basic knowledge of multimodality and multimodal interacttion.- Basic knowledge of the gestural interaction.- Basic knowledge of speech production and perception.- Basic knowledge of speech recognition, acoustic feature extraction, and sequence modeling.- Basic knowledge of audio-visual and multimodal speech recognition.- Basic knowledge of machine learning and data mining.- Basic knowledge of machine translation and dialogue systems.- Presentation and knowledge transfer skills. Students will be able to- use the learned knowledge for designing exemplary human-computer interfaces

Requirements for participation and examination Desirable prerequisites for participation in the courses: Basic knowledge of communications engineering and digital signal processing.


Module completion

Computer-Supported Interaction

Module title:

Computer-Supported Interaction

Credits:

3

Responsible person:

Möller, Sebastian

Office:

TEL 18

Contact person:

Hirsch, Tobias

Website:


Display language:

Englisch

E-mail address:

[email protected]



Learning Outcomes This course introduces the major ideas used today in the implementation of programming language compilers. Students will learn how aprogram written in a high-level language designed for humans translates into a program written in low-level assembly. Students will be able to:- Understand how real compilers work and how high-level language program are systematically translated into low-level assembly;- Become familiar with compiler analyses, intermediate representations and code generation;- Improve programming ability;- Implement compiler analysis, transformation and code generation approaches based on real compiler infrastructures;- Study recent advances in compiler design.

Requirements for participation and examination Desirable prerequisites for participation in the courses: - Knowledge of C programming- An introductory course on computer architecture is recommended


Module completion

Compiler Design

Module title:

Compiler Design

Credits:

6

Responsible person:

Juurlink, Bernardus

Office:

EN 12

Contact person:

Cosenza, Biagio

Website:

http://www.aes.tu-berlin.de

Display language:

Englisch

E-mail address:

[email protected]




Test description:Grading system 2 will be used.

Test elements Categorie Points Duration/Extent(Examination) Final test written 50 90 min(Deliverable assessment) 4 assigments, equally weighted practical 50 jeweils 3-4 Wochen


Lernergebnisse After visiting this module, deep skills in network protocol programming including handling of Linux based embedded systems andknowledge of the design of common wireless network controllers and their programming will be obtained. Attendees of this module will be inthe position to realize principles of telecommunication protocol mechanisms in real world applications. The emphasis lies on the design oflow level protocol mechanisms at the border between the physical and data link layer according to the ISO/OSI model.

Voraussetzungen für die Teilnahme / Prüfung Wünschenswerte Voraussetzungen für die Teilnahme an den Lehrveranstaltungen: k.A.



Network protocol programming lab

Titel des Moduls:

Network protocol programming lab

Praktikum Programmierung von Netzwerkprotokollen

Leistungspunkte:

6


Zubow, Anatolij

Sekretariat:

FT 5

Ansprechpartner:

Rathke, Berthold

Webseite:

http://www.tu-berlin.de/?108249#40276

Anzeigesprache:

Deutsch

E-Mailadresse:

[email protected]




Prüfungsbeschreibung:In total 100 Portfolio points can be obtained according to the table below.

The final module grade will be given according to the §47 (2) AllgStuPO, using grade scheme (Notenschlüssel) 2 of Faculty IV.

Prüfungselemente Kategorie Punkte Dauer/Umfang(Deliverable assessment) 7 Lab Assignments praktisch 60 14h ongoing(Examination) 2 Oral Consultations mündlich 30 à 30min(Examination) Written Test schriftlich 10 <90min


Learning Outcomes Within the last decade, telecommunication networks have undergone a huge transformation from voice to data transmission. This isreflected in a set of new protocols for data transmission as well as new control paradigms. Often these protocols are extensions of the well-known Ethernet and IP families that provide manageability, monitoring and reconfigurability. The advent of Software-Defined Networks(SDN) and Network Functions Virtualization (NFV) means that network operators require new programming skills to quickly understand andinfluence the behavior of a network under load or under attack.Students completing this module will be familiar with Telecom network protocols ranging geographically from the home router to the corenetwork.They will be able to configure primary and backup paths, write applications for the Open Network Operating System (ONOS) networkcontroller, and detect a mis-configured network device.

Requirements for participation and examination Desirable prerequisites for participation in the courses: BSc module „Kommunikationsnetze” or similar knowledge. Knowledge of architecture and programming of network systems is of benefit.


Module completion

High-speed Network Technologies with Lab

Module title:

High-speed Network Technologies with Lab

Credits:

6

Responsible person:

Zubow, Anatolij

Office:

FT 5

Contact person:

Woesner, Hagen

Website:

http://www.tu-berlin.de/?108249#40279

Display language:

Englisch

E-mail address:

[email protected]




Test description:The final module grade will be given according to the §47 (2) AllgStuPO, using grade scheme (Notenschlüssel) 2 of Faculty IV.

Test elements Categorie Points Duration/Extent(Deliverable assessment) PR Laboratory - 7 Labassignments, 2 points each

practical 14 14h ongoing

(Examination) VL High-speed Network Technologies - oralconsultation

oral 50 30min

(Examination) PR Laboratory - source code submission (viagitlab.tu-berlin.de)

practical 18 100-500 Zeilen Phyton Code

(Examination) PR Final Laboratory - presentation oral 18 30min


Learning Outcomes Students completing the module will gain the understanding of basic principles and technologies behind self-organizing wireless sensornetworks, through a balanced combination of lectures and practical work with modern sensor node hardware.

Requirements for participation and examination Desirable prerequisites for participation in the courses: BSc module „Kommunikationsnetze” or similar knowledge is required. Knowledge of architecture and programming of embedded systems isof benefit.


Module completion

Ad-hoc and Sensor Networks

Module title:

Ad-hoc and Sensor Networks

Credits:

6

Responsible person:

Zubow, Anatolij

Office:

FT 5

Contact person:

Handziski, Vlado

Website:

http://www.tkn.tu-berlin.de/?108248#adhsn

Display language:

Englisch

E-mail address:

[email protected]




Test description:In total 100 Portfolio points can be obtained. The final module grade will be given according to the §47 (2) AllgStuPO, using grade scheme(Notenschlüssel) 2 of Faculty IV. The individual grades will be obtained as specified in the table below.

Further details:

VL: Final lecture written test: The students take part in a < 90 min final test that checks the overall level of acquired knowledge from the AdHoc and Sensor Networks lecture.

PR: Lab assignments: Organized in small groups (3-4 persons), the students are asked to jointly absolve a set of lab assignments thatinvolve in-class programming assignments using state of the art sensor network hardware and software, and homework tasks (some ofthem individually, some of them as a group). Evaluated is the correctness of the provided answers, the correctness and the quality of thecode for the programming assignments. Each lab is assessed with a three-level scale: not-satisfactory, satisfactory and excellent.

PR: Final lab project: After the completion of the individual lab assignments, the lab groups are asked to design, develop and demonstratea relatively simple but complete sensor networks application that involves data acquisition, processing and communication. Evaluated isthe final "project presentation" (quality of the content and coverage, presentation organization and style, capability to answer follow-upquestions), and the "project demo" (general functionality, achievement of design goals, effective use of HW and SW, team work, codequality, documentation, effective use of version control tools).

PR: Final lab review: The students take part in a final review that checks the overall level of acquired knowledge from the Sensor NetworksLab. Evaluated is the familiarity with the Lab HW and SW and the familiarity with the the solutions of the individual Lab assignments.

Students are asked to self-evaluate the relative contribution of each team member as part of the team, which is considered in the formationof the final individual marks.

Test elements Categorie Points Duration/ExtentPR Sensor Networks Lab - Project presentation (Deliverableassessment)

oral 4 30 min

VL Ad-hoc and Sensor Networks - Final lecture written test(Examination)

written 50 90 min

PR Sensor Networks Lab - 7 Lab assignments, 3 pointseach (Deliverable assessment)

practical 21 7x (90 + 90) min

PR Sensor Networks Lab - Project demo (Deliverableassessment)

oral 5 30 min

PR Sensor Networks Lab - Final lab review (Learningprocess review)

written 20 45 min


Learning Outcomes The students will have an in-depth knowledge and hands-on experience on emerging fields of Robotics and Autonomous Systems (RAS)towards a smooth transition from theoretical knowledge to their applications in dynamic real-time environments. They will experience a fullR&D project cycle covering researching, setting-up, developing and finalizing (testing on real systems or on simulation). These will have adeeper insight into the scientific and technological aspects of existing solutions in artificial intelligence and multi-agent systems. Thestudents will experience various computer vision, learning and planning problems in RAS, will have improved programming skills (e.g.python / C++) in real applications and get familiar with Robotic Operating System (ROS).

Requirements for participation and examination Desirable prerequisites for participation in the courses: There are no specific prerequisites for this module. A general knowledge of programming (e.g. python, C/C++) and an overall interest inrobotics are sufficient.


Module completion

Applications of Robotics and Autonomous Systems

Module title:

Applications of Robotics and Autonomous Systems

Credits:

9

Responsible person:

Albayrak, Sahin

Office:

TEL 14

Contact person:

Görür, Orhan Can

Website:

http://www.aot.tu-berlin.de/index.php?id=2887

Display language:

Englisch

E-mail address:

[email protected]




Test description:Die Gesamtnote gemäß § 47 (2) AllgStuPO wird nach dem Notenschlüssel 2 der Fakultät IV ermittel.

Test elements Categorie Points Duration/ExtentErgebnisprüfung: Abschlusspräsentation und Review oral 20 90 MinutenErgebnisprüfung: Implementierung und Test practical 30 ca 3 WochenErgebnisprüfung: Evaluation und Dokumentation written 25 ca 2 WochenErgebnisprüfung: Design written 25 ca 2 Wochen


Lernergebnisse -

Voraussetzungen für die Teilnahme / Prüfung Wünschenswerte Voraussetzungen für die Teilnahme an den Lehrveranstaltungen: * An introductory course on computer architecture (e.g. "Rechnerorganisation") is recommended* Affinity to low-level programming



Advanced Computer Architecture

Titel des Moduls:

Advanced Computer Architecture

Rechnerorganisation Vertiefung

Leistungspunkte:

6


Juurlink, Bernardus

Sekretariat:

EN 12

Ansprechpartner:

Juurlink, Bernardus

Webseite:


Anzeigesprache:

Deutsch

E-Mailadresse:

[email protected]


100 Punkte insgesamtDeutsch



Prüfungselemente Kategorie Punkte Dauer/Umfang(Deliverable assessment) Practical Assignments(2x 15points, 2x 10 points)

praktisch 50 jeweils 3-4 Wochen

(Examination) Final Test schriftlich 50 90 min


Learning Outcomes The participants of this module will achieve deep conceptual, methodical, technical and practical knowledge in requirements analysis,design, architecture and development of heterogeneous and distributed information systems. This includes firstly classical knowledge aboutfederated databases and mediator-based information systems (tight or loose coupling wrt. the dimensions of distribution, heterogeneity andautonomy). Secondly, different paradigms of heterogeneous information infrastructures and their management (e.g. P2P) andinteroperability architectures (‘middleware’) will be investigated. Finally, modern model-based concepts for the development, integration andevolution of arbitrary information infrastructures, and –under this conceptual frame– model, metamodel, and metadata management as wellas semantic concepts will be discussed and brought into practical experience by some larger project-like group work.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Prerequisites: The basic modules in the Bachelor Curriculum in “Informatik”, or "Technische Informatik" or "Wirtschaftsinformatik" or"Wirtschaftsingenieurwesen"; particularly knowledge in Database Systems/ Information Modeling and Software Engineering / Programmingis required. The AIM-1 / HDIS course will be given in English language, thus fluency in English is required!


Module completion

Advanced Information Management 1 (AIM-1) - Heterogeneous and Distributed Information

Systems (HDIS)

Module title:

Advanced Information Management 1 (AIM-1) - Heterogeneous and DistributedInformation Systems (HDIS)

Credits:

6

Responsible person:

Kutsche, Ralf-Detlef

Office:

EN 7

Contact person:

Kutsche, Ralf-Detlef

Website:


Display language:

Englisch

E-mail address:

[email protected]




Test description:The grade will be given by fulfilling all required tasks during the course (portfolio exam): seminar work including the oral presentation andthe final report; home/lab exercises including presentation and the semester project including the final report/presentation.


Test elements Categorie Points Duration/Extent(Deliverable assessment) Written Seminar Report written 40 25 Seiten(Deliverable assessment) Homework Presentation oral 10 30 min(Deliverable assessment) Seminar Talk oral 25 60 min.(Deliverable assessment) Project Work: Software,Documentation, Presentation

practical 25 30 min. + 15 Seiten


Lernergebnisse Durch die technologischen Entwicklungen der letzten Jahre entstehen immer mehr Anwendungen, indenen kontinuierlich Daten produziert werden, die auch nur für eine gewisse Zeit aktuell bzw. gültig sind. Derartige Anwendungen sinddadurch gekennzeichnet, dass sie Ströme von Daten verarbeiten müssen.Die Teilnehmer dieses Moduls bekommen vertiefte konzeptionelle, methodische und praktischeKenntnisse für die Verarbeitung von Datenströmen an Beispielen aus den verschiedenenAnwendungsbereichen.

Voraussetzungen für die Teilnahme / Prüfung Wünschenswerte Voraussetzungen für die Teilnahme an den Lehrveranstaltungen: Diese Lehrveranstaltung wendet sich an Master-Studenten mit Schwerpunkt im BereichDatenbanksysteme und Informationsmanagement ab dem 1. (Master-)Semester. Die Voraussetzungensind das abgeschlossene Bachelorstudium und Kenntnisse der modernen Modellierungssprachen unddes klassischen Datenbankmanagements. Die Literatur für diese Veranstaltung ist in vielen Fällen inenglischer Sprache abgefasst, daher sind gute Englischkenntnisse erforderlich.



Advanced Information Management 2 - Management of Data Streams

Titel des Moduls:

Advanced Information Management 2 - Management of Data Streams

Leistungspunkte:

6


Markl, Volker

Sekretariat:

EN 7

Ansprechpartner:

Borusan, Alexander

Webseite:


Anzeigesprache:

Deutsch

E-Mailadresse:

[email protected]

Benotung: Prüfungsform: Sprache: Dauer/Umfang:benotet Mündliche Prüfung Deutsch ca. 40 Minuten


Learning Outcomes Recent advances in technology have led to rapid growth of big data. This led to the need for cost efficient and scalable analysis algorithms.In this course concepts for scalable analysis of big data sets will be presented and applied using open source technologies. Participants ofthis module will gain an in-depth understanding of concepts and methods as well as practical experience in the area of scalable datascience. The course is principally designed to impart: technical skills (50%), method skills (30%), system skills (10%), and social skills(10%).

Requirements for participation and examination Desirable prerequisites for participation in the courses: Computer science topics addressed in TU Berlin modules in the Bachelor’s curriculum, particularly, the database course (“InformationSystems and Data Analysis”) or the equivalent, as well as excellent JAVA AND SQL programming skills are strictly required. Basicknowledge in linear algebra, numerical analysis, probability, and statistics are strongly recommended. Furthermore, it is highly advisable ifstudents have already completed (or are currently enrolled in) a machine-learning course. Since the course will be offered in English,fluency in English is also required.


Module completion

Advanced Information Management 3 (AIM-3) Scalable Data Science: Systems & Methods

(SDSSM)

Module title:

Advanced Information Management 3 (AIM-3) Scalable Data Science: Systems& Methods (SDSSM)

Credits:

6

Responsible person:

Markl, Volker

Office:

EN 7

Contact person:

Soto, Juan

Website:

http://www.dima.tu-berlin.de/

Display language:

Englisch

E-mail address:

[email protected]




Test description:The portfolio exam (worth 100 points) is comprised of three parts, namely: (i) written homework (30 points), (ii) in-class presentations (20portfolio points), and (iii) a written exam (50 portfolio points).


Test elements Categorie Points Duration/Extent(Examination) Written test written 50 75 min.(Deliverable assessment) In-class presentations oral 20 40 min. / about 35 slides(Deliverable assessment) Homework written 30 30 hours / 20 pages


Learning Outcomes Graduates of this module have experience with methods and techniques for the analysis of embedded systems and how these systems canbe optimized for special architectures. They have a general conceptual and formally well founded understanding of program analysis andare able to specify and implement different concrete program analyses. They are also able to apply their knowledge on new problems ondifferent levels of abstraction (e.g. code vs. system architecture). Furthermore, they are able to analyze the range of optimizationpossibilities towards a given optimization goal and to construct suitable analyses and optimizations.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Knowledge in the basics of software engineering for embedded Systems (as teached in the Software Engineering Eingebetteter Systemebachelor course) are benefical.

Mandatory requirements for the module test application:

Module completion

Analysis and Optimization of Embedded Systems

Module title:

Analysis and Optimization of Embedded Systems

Credits:

6

Responsible person:

Glesner, Sabine

Office:

TEL 12-4

Contact person:

Klös, Verena

Website:

No information

Display language:

Englisch

E-mail address:

[email protected]

1.) Homework in training course Analysis and Optimization of Embedded Systems

Grading: Type of exam: Language: Duration/Extent:graded Oral exam English 30 min


Learning Outcomes Knowledge and practical experiences in the realm of designing embedded processor architectures and its programming are gained.Students are able to plan, coordinate and carry out hardware/software co-design, programming in hardware description languages andsystem-level programming, as well as team management and coordination in a project. The course is principally designed to imparttechnical skills 35%, method skills 15%, system skills 15%, social skills 35%

Requirements for participation and examination Desirable prerequisites for participation in the courses: Knowledge about computer architecture and hardware description languages (VHDL or Verilog) are obligatory (e.g. Technische Grundlagender Informatik 2 (TechGI2)). Desirable are practical experiences in synthesis of hardware descriptions or microcontroller or system-levelprogramming.


Module completion

Applied Embedded Systems Project

Module title:

Applied Embedded Systems Project

Credits:

6

Responsible person:

Juurlink, Bernardus

Office:

EN 12

Contact person:

Juurlink, Bernardus

Website:


Display language:

Englisch

E-mail address:

[email protected]




Test description:Grading system 2 will be used:

95% or more1.090% or more1.385% or more1.780% or more2.075% or more2.370% or more2.765% or more3.060% or more3.355% or more3.750% or more4.0Less than 50%5.0

Test elements Categorie Points Duration/Extent(Deliverable assessment) Implementation practical 40 semesterbegleitend(Deliverable assessment) Project documentation,presentation(s), etc

written 35 jeweils 2 Wochen

(Learning process review) Participation in project work practical 25 semesterbegleitend


Learning Outcomes Participants of this seminar will acquire knowledge about recent research results and trendsin the analysis of web-scale data. Through the work in this seminar, students will learn thecomprehensive preparation and presentation of a research topic in this field. In order toachieve this, students will get to read and categorise a scientific paper, conductbackground literature research and present as well as discuss their findings.After the course, students will be able to critically read and evaluate scientific publications,and to conduct background research. They will be capable of preparing for and giving oralpresentations on research topics for an expert audience, of analyzing the state of the art of aresearch topic, and of summarizing it in a scientific paper. They should also understandtechniques used in the scientific community like peer reviews, conference presentations, anddefenses of the findings after their presentation, as well as they should understand methodsfor large-scale data analytics. The course is principally designed to impart:Technical skills: 50x Methodological skills: 20x System skills: 10x Social skills: 20x

Requirements for participation and examination Desirable prerequisites for participation in the courses: This course is aimed at master students with a focus on database systems and information management and should be chosen after the2nd master semester. To be able to participate you should have successfully completed 'Database Technology DBT' and one of the'Advanced Information Management AIM' (1,2,3) courses.In the ideal case this seminar should be taken by students who are directly in front of their master thesis, or have already completed it andare interested in a doctorate in information management.It is vital that you have a sound understanding of written and spoken English.


Module completion

BDASEM - Big Data Analytics Seminar

Module title:

BDASEM - Big Data Analytics Seminar

Credits:

3

Responsible person:

Markl, Volker

Office:

EN 7

Contact person:

Rabl, Tilmann

Website:

http://www.dima.tu-berlin.de/

Display language:

Englisch

E-mail address:

[email protected]




Test description:The exam will be done as a 'portfolio examination', including two deliverable assessments, totaling for 100 portfolio points:- 2 seminar presentations (50 portfolio points)- 2 written seminar reports (50 portfolio points)Cf. the details in the resp. fields, and follow the instructions in the beginning of the class.


Test elements Categorie Points Duration/Extent(Deliverable assessment) long written seminar report written 40 10-15 pages(Deliverable assessment) presentation 1 oral 20 20 min(Deliverable assessment) presentation 2 oral 30 30 min.(Deliverable assessment) short written seminar report/s written 10 4-6 pages in total


Lernergebnisse - Expertise to assess existing and future approaches to identify and verify users- Knowledge of current technical approaches to classify biometrical features- Ability to do critical (online) literature research- Presentation skills

Voraussetzungen für die Teilnahme / Prüfung Wünschenswerte Voraussetzungen für die Teilnahme an den Lehrveranstaltungen: Desirable: Basic signal processing skills and/or usability engineering knowledge



Biometric Identification

Titel des Moduls:

Biometric Identification

Biometrische Identifikation

Leistungspunkte:

3


Möller, Sebastian

Sekretariat:

TEL 18

Ansprechpartner:

Hirsch, Tobias

Webseite:


Anzeigesprache:

Deutsch/Englisch

E-Mailadresse:

[email protected]




Prüfungsbeschreibung:

Multiple Choice Tests: On three specific dates there is a multiple choice test around the topics dealt with during the seminar.

Programming Homeworks: During tutorial sessions student start to solve different programming exercises related to the seminar topics.The students finish the exercises at home and hand in the solutions for each question of the exercise.

Oral Presentation: Based on a given topic the students hold presentations either individually or in small groups.

Written Version: The students write a short scientific paper on the same topic as for the presentation.

Prüfungselemente Kategorie Punkte Dauer/Umfang(Deliverable assessment) 3 programming homeworks à 2 x8 points, 1 x 6 points

praktisch 22 1-2 programming exercisesper homework

(Deliverable assessment) Oral Presentation mündlich 30 22 min(Deliverable assessment) Written Version schriftlich 30 2 pages(Examination) 3 multiple choice tests each 6 points schriftlich 18 15 min


Learning Outcomes Students possess knowledge of the principles and characteristics of cloud computing at the practical, as well as, the theoretical level.Furthermore they understand critical questions and current solutions in this area.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Knowledge of the principles of distributed systems are required. Good programming skills are beneficial.


Module completion

Cloud Computing

Module title:

Cloud Computing

Credits:

6

Responsible person:

Kao, Odej

Office:

EN 59

Contact person:

No information

Website:

http://www.cit.tu-berlin.de

Display language:

Englisch

E-mail address:

[email protected]




Test description:The final exam is based on the results in the group assignments and the written test.

Test elements Categorie Points Duration/Extent(Deliverable assessment) Assignments practical 40 Five weeks(Examination) Test written 60 60 minutes


Lernergebnisse -

Voraussetzungen für die Teilnahme / Prüfung Wünschenswerte Voraussetzungen für die Teilnahme an den Lehrveranstaltungen: -Basic knowledge of digital design and digital design process.-Basic knowledge of number systems and number representation of digital computers.-knowledge of VHDL/FPGA is an advance.



Computer Arithmetic: Circuit Perspective

Titel des Moduls:

Computer Arithmetic: Circuit Perspective

Computerarithmetik: Schaltkreisperspektive

Leistungspunkte:

6


Juurlink, Bernardus

Sekretariat:

EN 12

Ansprechpartner:

Juurlink, Bernardus

Webseite:


Anzeigesprache:

Deutsch

E-Mailadresse:

[email protected]




Prüfungsbeschreibung:Grading system 2 will be used.

Prüfungselemente Kategorie Punkte Dauer/Umfang(Deliverable assessment) Assignments (5x, each 4 points) schriftlich 20 jeweils 2 Wochen(Deliverable assessment) Quiz schriftlich 5 20 min(Examination) Final Test schriftlich 35 90 min(Learning process review) Lab work (4x, each 10 points) praktisch 40 jeweils 2 Wochen


Learning Outcomes Students have an in-depth understanding of computer graphics. They are able to present and convey their acquired knowledge and skillsconvincingly.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Basic knowledge of computer graphics is required, such as the contents of the Master module Computer Graphics I. Knowledge in linearalgebra, scientific computing, and algorithms/data structures is recommended.


Module completion

Computer Graphics Seminar A

Module title:

Computer Graphics Seminar A

Credits:

3

Responsible person:

Alexa, Marc

Office:

MAR 6-6

Contact person:

Fer-Arslan, Gaelle

Website:

http:// http://www.cg.tu-berlin.de

Display language:

Englisch

E-mail address:

[email protected]




Test description:In compliance with § 47 (2) AllgStuPO, the overall grade is calculated according to the scoring system 1 of the Faculty IV.

Implementation, talks (interim and final presentations) and seminar documentation can be carried out in German or English.

1. Implementation: The students work on a selected question and develop a prototypical implementation based on their findings.2. Tech-presentation: The students present a technical aspect of their work and give oral replies to respective questions.3. Interim presentation: The students orally present their first findings and the interim results on their topic and give oral replies torespective questions.4. Final presentation: The students orally present their final findings and the final results of their seminar documentation and give oralreplies to respective questions.5. Seminar documentation: The students summarize their final findings, application methods and final results in a written seminardocumentation.

Test elements Categorie Points Duration/Extent1. Implementation (Deliverable assessment) practical 40 Project Implementation2. Tech Presentation flexible 10 approx. 15 minutes

(presentation + questions)3. Interim Presentation (Deliverable assessment) flexible 10 approx. 15 minutes

(presentation + questions)4. Final Presentation (Deliverable assessment) flexible 20 approx. 20 minutes

(presentation + questions)5. Seminar Documentation (Deliverable assessment) written 20 Website


Learning Outcomes No information

Requirements for participation and examination Desirable prerequisites for participation in the courses: This course is the base course for master students with focus on database systems and information management and should be attendedin the first semester of the master program. In contrast to the introduction of database systems(MPGI5/DBS/Informationssystemse&Datenanalyse), which looks at database systems from an application programmers point of view, thisclass focuses on the internals of database systems. To participate, students are required to have successfully completed a Bachelor incomputer science with a focus on database systems (participation in the Datenbankpraktikum, Datenbankprojekt). Knowledge of datamodeling, relational algebra, and SQL as well as a very good command of Java, or possibly C/C++/C#, programming is required toparticipate in the course. Due to capacity reasons, the class is limited to at most 60 participants.


Module completion

DBT: Database Technology

Module title:

DBT: Database Technology

Credits:

6

Responsible person:

Markl, Volker

Office:

EN 7

Contact person:

Markl, Volker

Website:


Display language:

Englisch

E-mail address:

[email protected]





Test elements Categorie Points Duration/Extent(Deliverable assessment) Assessment of 4 homeworkexercises with 5 pts.

written 20 about 10h / around 25questions each

(Examination) End term test written 45 60 minutes(Examination) Mid term test written 35 60 minutes


Learning Outcomes Students who have successfully finished this module have an overview of current and future concepts for digital communities. They havedeveloped an understanding of the principles of graph theory, concepts of network analysis, and principles of social network analysis, andhave learned about the concepts of recommender systems. They are also aware of the limitations and privacy issues of concepts andapplications in digital communities.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Mandatory: basic knowledge of computer science.Desirable: knowledge of graph theory and linear algebra, basic programming skills.


Module completion

Digital Communities

Module title:

Digital Communities

Credits:

6

Responsible person:

Küpper, Axel

Office:

TEL 19

Contact person:

Ruppel, Peter

Website:

http://www.snet.tu-berlin.de/digitalcommunities

Display language:

Englisch

E-mail address:

[email protected]



Learning Outcomes Participants learn basic concepts, their theoretical foundation, and the most common algorithms used in digital image processing. Aftercompleting the module, participants understand strengths and limitations of different methods, are able to correctly and successfully applymethods and algorithms to real world problems, and are aware of performance criteria. More specifically, participants will be able to demonstrate 1) Knowledge of theory and methods of signal processing2) Application to problems of image enhancement and image restoration3) Understanding regarding concepts of feature extraction

Requirements for participation and examination Desirable prerequisites for participation in the courses: none


Module completion

Digital Image Processing

Module title:

Digital Image Processing

Credits:

6

Responsible person:

Hellwich, Olaf

Office:

MAR 6-5

Contact person:

Dennert, Marion

Website:

http://www.cv.tu-berlin.de/

Display language:

Englisch

E-mail address:

[email protected]

Grading: Type of exam: Language: Duration/Extent:graded Written exam English 90 minutes


Learning Outcomes Students who have successfully finished this module know the most important basic algorithms for distributed systems and their respectiveproperties. They know typical structures of distributed algorithms and can evaluate the complexity, scalability and fault tolerance properties.The students can apply their knowledge for selecting appropriate algorithms while designing distributed systems.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Basic skills in distributed systems. Sufficient knowledge about the contents of both courses "Systemprogrammierung" and "Rechnernetzeund verteilte Systeme"or both courses "Technische Grundlagen der Informatik für Wirtschaftsinformatiker" and "Programmierpraktikum".


Module completion

Distributed Algorithms

Module title:

Distributed Algorithms

Credits:

6

Responsible person:

Hauswirth, Manfred

Office:

HFT 3

Contact person:

Le Phuoc, Danh

Website:

http://www.ods.tu-berlin.de

Display language:

Englisch

E-mail address:

[email protected]

1.) [KBS] Distributed Algorithms Assignments

Grading: Type of exam: Language: Duration/Extent:graded Written exam English 90 Minuten


Learning Outcomes Students who have successfully finished this module have an advanced knowledge of operating systems for embedded systems. They areaware of the specific design aspects (like realtime behavior, energy consumption, schedulability, fault tolerance) and know of theirinterdependencies.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Basic (undergraduate) course on operating systems is required to follow the lectures.


Module completion

Embedded Operating Systems

Module title:

Embedded Operating Systems

Credits:

6

Responsible person:

Heiß, Hans-Ulrich

Office:

EN 6

Contact person:

No information

Website:

http://www.kbs.tu-berlin.de/

Display language:

Englisch

E-mail address:

[email protected]

Grading: Type of exam: Language: Duration/Extent:graded Oral exam English 30 minutes



Requirements for participation and examination Desirable prerequisites for participation in the courses: Prerequisites:• knowledge equivalent to the "Software Security" lecture• familiarity with Unix/Linux operating system primitives (e.g. using a command line) Recommended additional skills:• basic networking concepts and tools (DNS, DHCP, NAT, ...)• low-level programming concepts (pointers, registers, stack vs. heap, ...)• basic concepts of cryptography In order to complete the assignments, each participant needs at least one computer with administrator privileges (i.e. being able to log intouniversity computers is insufficient) preferrably running Linux. It is possible to complete the tasks while using Windows or MacOS as well,but the teaching staff cannot provide guidance on those operating systems.


Module completion

Embedded Systems Security Lab

Module title:

Embedded Systems Security Lab

Credits:

6

Responsible person:

Seifert, Jean-Pierre

Office:

TEL 17

Contact person:

Nordholz, Jan Christoph

Website:

http://www.isti.tu-berlin.de/security_in_telecommunications/menue/teaching/courses/security_lab/

Display language:

Englisch

E-mail address:

[email protected]


100 points per elementEnglish


Test description:• (Practical Course) 6 practical assignments

Test elements Categorie Weight Duration/Extent(deliverable assessment) 1 assignment (group work) practical 1 2 weeks(deliverable assessment) 5 assignments (individual work) practical 5 2 weeks each


Learning Outcomes As part of a large system development project the students get the opportunity to systematically analyse, model and develop (problem-oriented) a solution for a hot topic in information management. They are able to operate as a team member and are responsible for projectorganization, quality assurance and documentation. Overall, the quality of the solution and the development should be done throughtheoretical analysis, systematic experiments and tests.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Entrance requirement for the project is the successful completion of the module DBT - Database Technology (or equivalent).


Module completion

IMPRO - Project Hot Topics in Information Management

Module title:

IMPRO - Project Hot Topics in Information Management

Credits:

6

Responsible person:

Markl, Volker

Office:

EN 7

Contact person:

Hemsen, Holmer

Website:


Display language:

Englisch

E-mail address:

[email protected]





Test elements Categorie Points Duration/Extent(Deliverable assessment) final presentation oral 10 20 minutes(Learning process review) presentation of project poster oral 10 about 20 minutes(Learning process review) active collaboration in projectteam work (incl. adherence to the scheduled progress plan)

practical 10 about 20h

(Deliverable assessment) final project report written 10 about 15h / 15 pages(Deliverable assessment) modelling and development of theprototype (incl. test cases)


(Deliverable assessment) documentation written 10 about 15h


Learning Outcomes In this course you will learn to systematically analyze a current issue in the information managementarea and to develop and implement a problem-oriented solution as part of a team. You will learn tocooperate as team member and to contribute to project organization, quality assurance and documentation. The quality of your solution hasto be proven through analysis, systematic experiments and test cases. Examples of IMPRO projects carried out in recent semesters are atool used to analyse Web 2.0 Forum data, an online multiplayer game for mobile phones, implementation and analysis of new join methodsfor a cloud computing platform or the development of data mining operations on the massively parallel system Hadoop as part of theApache open source project Mahout.After the course, students will be able to understand methods for large scale data analytics and tosolve large scale data analytics problems. They will be capable of designing and implementing largescale data analytics solutions in a collaborative team.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Knowledge from the complete Bachelor program (Informatik or Technische Informatik) is required, aswell as linear algebra and statistics. Depending on the topic, additional prerequisites may be required, e.g. „DBT - Database Technology" Solid programming skills in at least one of the following programming languages: Java, C++, Scala, Python.Basic knowledge in functional programming.Basic knowledge in distributed source control management systems (Git, Mercurial) and software processes like Scrum.


Module completion

BDAPRO - Big Data Analytics Project

Module title:

BDAPRO - Big Data Analytics Project

Credits:

9

Responsible person:

Markl, Volker

Office:

EN 7

Contact person:

Alexandrov, Alexander

Website:


Display language:

Englisch

E-mail address:

[email protected]




Test description:The overall grade for the module consists of the results of the course work ('portfolio exam'). The following are included in the final grade:1. Prototype with test cases and documentation (30p.)2. Experiment design and execution (20p.)3. Intermediate presentation (10p.)4. Experiments analysis (20p.)5. Final presentation (20p.)


Test elements Categorie Points Duration/Extent(Deliverable assessment) Final presentation oral 20 about 20 minutes(Deliverable assessment) Intermediate presentation oral 10 about 10-15 minutes(Learning process review) Experiment design and execution practical 20 about 30h(Learning process review) Prototype with test cases anddocumentation


(Deliverable assessment) Experiments analysis practical 20 about 30h


Learning Outcomes After completing this moldule, the participants have gained practical experience in designing, implementing, and testing of applications forthe internet of services within a small team and therefore gained significant knowledge and insights within the areas of mobile devices,communication and services, location-based services, cloud computing and digital communities. Furthermore, the participants have gainedimportant knowledge of how to organize and realize IT projects, including controlling, reporting, planning, and communicating with externalpartners.

Requirements for participation and examination Desirable prerequisites for participation in the courses: - Programming skills- Communication skills in english- Autonomous working style- Basic knowledge in the area of the chosen task


Module completion

Internet of Services Lab

Module title:

Internet of Services Lab

Credits:

9

Responsible person:

Küpper, Axel

Office:

TEL 19

Contact person:

Grunert, Kai

Website:

http://www.snet.tu-berlin.de/internet-of-services

Display language:

Englisch

E-mail address:

[email protected]




Test description:All in all 100 portfolio points can be achieved:

The final grade under the terms of § 47 (2) AllgStuPO is calculated according to the grading scheme no. 2 of faculty IV.

* Practical Implementation: the outcome of the project is assessed. For that the annotated source code, the reusability, the quality and thequantity of the resulting software is evaluated.

* Milestone Presentations: the presentation of the project in front of the whole course is assessed. For that the structure, presentation andlinguistic style, the slide design, the selected topics, the time management and the Q&A session is evaluated.

* Written Report: a written report that contains a description of the project is assessed. For that the structure, the completeness, theevaluation and the scientific working is assessed.

* Process of the Project: the process and progression of the project is assessed in regular meetings with the supervisor. For that theapproach, the project management methods, the motivation, the independent work, the time managment, the task distribution, the teamcollaboration, the communication with the supervisors, the conflict resolution, the self-reflection, the creativity, the application ofknowledge, the clarification of the task and the analytical thinking is assessed.

Test elements Categorie Points Duration/Extent(Ergebnisprüfung) Milestone Presentations oral 25 20 - 30 min(Lernprozessprüfung) Process of the Project practical 25 weekly project work(Ergebnisprüfung) Practical Implementation practical 25 final software product(Ergebnisprüfung) Written Report written 25 25 - 50 pages


Lernergebnisse The general idea of this module is to give an introduction to approaches that uses features or processes of the human body as an input toobtain information that are otherwise difficult to access in the context of human-computer-interaction (HCI). - Basic understanding of neuronal processes and the relation of body regulation, emotion, cognition, and behavior.- Knowledge of current approaches in (evolutionary) psychology and neuroscience to emotions/affects.- Basic understanding of relevant physiological indicators of psychic processes- Expertise to assess existing and future approaches oto utilize bio/body signals in HCI and usablity research oto collect and analyze information about the user's current emotional state oto manipulate the user's mood oto identify and verify users- Ability to do critical (online) literature research- Presentation skills- Hands-on experience in an independent student research project

Voraussetzungen für die Teilnahme / Prüfung Wünschenswerte Voraussetzungen für die Teilnahme an den Lehrveranstaltungen: Keine Angabe



Introduction to Physiological Computing

Titel des Moduls:

Introduction to Physiological Computing

Leistungspunkte:

6


Möller, Sebastian

Sekretariat:

TEL 18

Ansprechpartner:

Hirsch, Tobias

Webseite:


Anzeigesprache:

Deutsch/Englisch

E-Mailadresse:

[email protected]





PJ Neuro-Usability - project plan: The students are expected to make a proposal for a project as well as provide a time plan and division oftasks within the project

PJ Neuro-Usability - project mid term presentation: This is a slide deck that must be provided to showcase the progress, issues and layoutthe plan for the rest of the project.

PJ Neuro-Usability - project presentation: A final presentation will be presented where the students present results, and connect to othersimilar work.

SEM Affective Computing - oral presentation: Based on a given topic the students hold presentations either individually or in small groups.

SEM Affective Computing - handout: The students write a short scientific paper on the same topic as for the presentation.

SEM Affective Computing - written test: The final exam is problem solving oriented, requiring the students too apply the learnt theory toreal problems and provide a plan, to solve these problems.


Prüfungselemente Kategorie Punkte Dauer/Umfang(Deliverable assessment) PJ Neuro-Usability: project finalpresentation

mündlich 20 30 min

(Deliverable assessment) PJ Neuro-Usability: project midterm presentation

mündlich 20 30 min

(Deliverable assessment) PJ Neuro-Usability: project plan schriftlich 5 5 pages(Deliverable assessment) SEM Affective Computing:handout

schriftlich 15 15 pages

(Deliverable assessment) SEM Affective Computing: oralpresentation

mündlich 15 30 min

(Examination) SEM Affective Computing: written test schriftlich 25 90 min


Learning Outcomes * general understanding of basic principles of acoustics, audio technology and auditive perception* basic knowledge of recording, coding, transmission and playback of speech and audio signals* basic knowledge of room acoustics, electro acoustics and psycho acoustics* basic knowledge of hearing, hearing perception and the human auditory system

Requirements for participation and examination Desirable prerequisites for participation in the courses: Als Voraussetzungen werden Grundkennnisse der Signalverarbeitung und der Physik als hilfreich gesehen, allerdings sind recht geringeKenntnisse ausreichend. Zu beiden Themen wird jeweils ein einführendes Grundlagenkapitel Bestandteil des Kurses sein.


Module completion

Communication acoustics

Module title:

Communication acoustics

Credits:

6

Responsible person:

Möller, Sebastian

Office:

TEL 18

Contact person:

Hirsch, Tobias

Website:


Display language:

Englisch

E-mail address:

[email protected]



Learning Outcomes The success of computer and communication systems strongly depends on their performance, typically reflected in the perception ofservice quality. Optimizing system performance, subject to a set of resource and cost constraints, is thus a critical design goal for systemengineers. Performance evaluation allows us to quantify the service delivered by systems as well as the usage of resources. Thus, studentscompleting this module will gain the understanding of basic concepts of performance evaluation of computer communication systems. Theywill become familiar with the basics of analytical, experimental and simulative methods, as well as approaches to experiment planning.Students will also be able to understand application of these methods to computer networks and distributed systems. Finally, they will beable to design and execute performance evaluation and comparison of systems form the performance point of view.

Requirements for participation and examination Desirable prerequisites for participation in the courses: BSc module „Kommunikationsnetze” or similar knowledge is required.


Module completion

Performance Evaluation of Computer Communication Systems

Module title:

Performance Evaluation of Computer Communication Systems

Credits:

6

Responsible person:

Zubow, Anatolij

Office:

FT 5

Contact person:

Zubow, Anatolij

Website:

http://www.tkn.tu-berlin.de/?108248#kstkn

Display language:

Englisch

E-mail address:

[email protected]





Test elements Categorie Points Duration/Extent(Deliverable assessment) Project work/ report practical 20 20h/ ~20 Seiten(Examination) Oral consultation oral 65 30min(Learning process review) Project presentation/ discussion oral 15 30min


Lernergebnisse Die Studierenden sind in der Lage, eigenständig die wesentlichen Verfahren des maschinellen Lernens auf neuen Daten anzuwenden. Diesumfasst Methoden zur Klassifikation, Regression, Dimensionsreduktion und Clustering. Darüber hinaus vermittelt das Modul dastheoretische Rüstzeug (Wahrscheinlichkeitstheorie, Optimierungstheorie), um Verfahren weiterzuentwickeln und theoretisch zu analysieren.

Voraussetzungen für die Teilnahme / Prüfung Wünschenswerte Voraussetzungen für die Teilnahme an den Lehrveranstaltungen: Programmierkenntnisse, gute Grundlagen in Mathematik, insbesondere Lineare Algebra, Analysis, Wahrscheinlichkeitsrechnung. DiesesModul ist auch für Bachelorstudierende geeignet.



Machine Learning 1

Titel des Moduls:

Machine Learning 1

Maschinelles Lernen 1

Leistungspunkte:

6


Müller, Klaus-Robert

Sekretariat:

MAR 4-1

Ansprechpartner:

Keine Angabe

Webseite:

https://wiki.ml.tu-berlin.de/wiki/

Anzeigesprache:

Deutsch

E-Mailadresse:

[email protected]

Benotung: Prüfungsform: Sprache: Dauer/Umfang:benotet Schriftliche Prüfung Deutsch/Englisch 120 Minuten


Learning Outcomes Students who have successfully finished this module have an overview of current and future services and service infrastructures in theMobile Internet. They have developed an understanding of the special characteristics of mobile networks - compared to fixed infrastructures- and have learned about the benefits of mobile services and the fascinating prospects of emerging areas such as Location-based Servicesand Ubiquitous Computing. However, they are also aware of the problems and limits of mobile service provisioning and know how to copewith these deficiencies when designing them. Furthermore, they have good knowledge of different alternatives of realizing services (forexample, device versus network centric approaches) and an overview of related service platforms, auxiliary functions, and operatingsystems of mobile devices.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Mandatory: basic knowledge of computer science and Internet/network architecturesDesirable: knowledge of distributed systems


Module completion

Mobile Services

Module title:

Mobile Services

Credits:

6

Responsible person:

Küpper, Axel

Office:

TEL 19

Contact person:

Rodriguez Garzon, Sandro

Website:

http://www.snet.tu-berlin.de/moses

Display language:

Englisch

E-mail address:

[email protected]



Lernergebnisse -

Voraussetzungen für die Teilnahme / Prüfung Wünschenswerte Voraussetzungen für die Teilnahme an den Lehrveranstaltungen: An introductory course on computer architecture (e.g. TechGI 2 or Rechnerorganisation), good programming skills, preferably in C/C++.



Multicore Systems

Titel des Moduls:

Multicore Systems

Mehrkernsysteme

Leistungspunkte:

6


Juurlink, Bernardus

Sekretariat:

EN 12

Ansprechpartner:

Juurlink, Bernardus

Webseite:


Anzeigesprache:

Deutsch

E-Mailadresse:

[email protected]





Prüfungselemente Kategorie Punkte Dauer/Umfang(Deliverable assessment) 5 assignments (weighted 15, 12,10, 8 and 5 points)

schriftlich 50 jeweils 3 Wochen

(Examination) Final Test schriftlich 50 90 min


Learning Outcomes The students know the basic principles, algorithms and architectures of computer networks. They are able to understand complexcorrelations and to interpret results of simulations. The goal is to master the basics of communications in computer networks, who hopefullyhave a long half-life period. This means that the discussed principles outlast current mainstreams.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Knowledge of the compulsory modules of Bachelor studies is mandatory.Desirable: good English language skills.


Module completion

Network Architectures - Basics

Module title:

Network Architectures - Basics

Credits:

6

Responsible person:

Zinner, Thomas Erich

Office:

MAR 4-4

Contact person:

Enghardt, Theresa

Website:

http://www.inet.tu-berlin.de/

Display language:

Englisch

E-mail address:

thomashttps://moseskonto.tu-berlin.de/moses/modultransfersystem/bolognamodule/ansehen.html?number=40590#[email protected]

1.) Hausaufgaben Network Protocols and Architectures

Grading: Type of exam: Language: Duration/Extent:graded Written exam German/English 120 Min


Lernergebnisse After successful completion of the project the students are capable of solving small tasks on their own. This includes background research,documentation and management of the project.

Voraussetzungen für die Teilnahme / Prüfung Wünschenswerte Voraussetzungen für die Teilnahme an den Lehrveranstaltungen: Knowledge of the compulsory modules of Bachelor studies and the Master module “Network architectures - basics” is mandatory.Desirable: good English language skills.



Network Architectures - Master Project

Titel des Moduls:

Network Architectures - Master Project

Netzwerkarchitekturen - Master Projekt

Leistungspunkte:

12



Sekretariat:

MAR 4-4

Ansprechpartner:

Enghardt, Theresa

Webseite:


Anzeigesprache:

Deutsch

E-Mailadresse:

[email protected]




Prüfungsbeschreibung:Overall, there are 100 (points) Portfoliopunkte:- practical part including the thesis (70 points)- presentation (30 points)

The grade will be determined based on the grading scheme 2 from department IV.

Prüfungselemente Kategorie Punkte Dauer/UmfangPractical part including report praktisch 70 6 MonatePresentation mündlich 30 30 Min


Learning Outcomes This lab course (Praktikum) trains in the configuration of networking components like switches and routers. After a successful completionthe students are capable of configuring routing protocols and policies, setting up VLANs and basic IPv4 / IPv6 networks as well astroubleshooting basic problems arising in that context.Likewise experiment planning, setup and performance are taught.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Good knowledge of the Master module “Network architectures - basics” (or equivalent) and the ability towork with the Linux command line as well as scripting languages is required. Fulfillment of therequirements has to be proven prior to admissionDesirable: good English language skills.


Module completion

Network Architectures - RouterLab

Module title:

Network Architectures - RouterLab

Credits:

9

Responsible person:


Office:

MAR 4-4

Contact person:

No information

Website:


Display language:

Englisch

E-mail address:

[email protected]




Test description:Successful participation in the lab course (Praktikum) requires continuous attendance and activeparticipation, accepted solutions of the work sheets.The grade will be determined by the weighted average grades of all solutions (Portfolioprüfung). Students need a minimum totalpercentage, to pass the lab course.

The oral test will take place after the first two (ungraded) lab assignments, and will be based on their content. Ongoing worksheets will behanded in weekly and discussed in review meetings, which are part of the examination elements.

Test elements Categorie Points Duration/Extent(Examination) Oral test oral 12 30 Minuten(Learning process review) 8 lab assignments with reviewmeetings, 11 points each

practical 88 20 Minuten


Lernergebnisse The successful completion of the seminar enables the participants to understand recent, complex, and professional literature and tosummarize the work. Furthermore, every participant acquires profound knowledge in his/her small topic.

Voraussetzungen für die Teilnahme / Prüfung Wünschenswerte Voraussetzungen für die Teilnahme an den Lehrveranstaltungen: Mandatory is the compulsory module "TechGI4 Rechnernetze und Verteilte Systeme", Desirable: good English language skills, the module"Network Architectures - Basics"



Network Architectures - Seminar

Titel des Moduls:

Network Architectures - Seminar

Netzwerkarchitekturen - Seminar

Leistungspunkte:

3



Sekretariat:

MAR 4-4

Ansprechpartner:

Enghardt, Theresa

Webseite:


Anzeigesprache:

Deutsch

E-Mailadresse:

[email protected]





Prüfungselemente Kategorie Punkte Dauer/Umfangpresentation mündlich 50 30 Minseminar paper schriftlich 50 1 semester


Learning Outcomes The goal is to understand the theoretical background and technical details of the respective lecture (routing, security, measurement) as wellas the basics of the whole range of topics. Illustrative examples deepen the comprehension such that a practical implementation of the topicat hand is obvious. These lectures are the basis on which projects and theses can be built upon. Furthermore, every participant acquiresprofound knowledge in his confined topic.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Good knowledge of the compulsory modules of Bachelor studies and the Master module "Network architectures - basics" is mandatory.Desirable: good English language skills.


Module completion

Network Architectures Specialization (big)

Module title:

Network Architectures Specialization (big)

Credits:

9

Responsible person:


Office:

MAR 4-4

Contact person:

Enghardt, Theresa

Website:


Display language:

Englisch

E-mail address:

[email protected]

Grading: Type of exam: Language: Duration/Extent:graded Oral exam German/English 30 min


Learning Outcomes The goal is to understand the theoretical background and technical details of the respective lecture (routing, security, measurement) as wellas the basics of the whole range of topics. Illustrative examples deepen the comprehension such that a practical implementation of the topicat hand is obvious. These lectures are the basis on which projects and theses can be built upon. Furthermore, every participant acquiresprofound knowledge in his confined topic.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Good knowledge of the compulsory modules of Bachelor studies and the Master module "Network architectures - basics" is mandatory.Desirable: good English language skills.


Module completion

Network Architectures Specialization (small)

Module title:

Network Architectures Specialization (small)

Credits:

6

Responsible person:


Office:

MAR 4-4

Contact person:

Enghardt, Theresa

Website:


Display language:

Englisch

E-mail address:

[email protected]

Grading: Type of exam: Language: Duration/Extent:graded Oral exam German/English No information


Learning Outcomes Students completing this module have gained understanding of the basic principles and technologies behind networked embeddedsystems.

Requirements for participation and examination Desirable prerequisites for participation in the courses: The course assumes founded knowledge in networking (e.g., BSc module Kommunikationsnetze), operating systems (e.g. Linux, TinyOS)and embedded programming (e.g. C, C++).


Module completion

Networked Embedded Systems

Module title:

Networked Embedded Systems

Credits:

6

Responsible person:

Zubow, Anatolij

Office:

FT 5

Contact person:

Handziski, Vlado

Website:

http://www.tkn.tu-berlin.de/?108248#nes

Display language:

Englisch

E-mail address:

[email protected]





Further details:

IV: In-class presentation: Each student is asked to prepare one ~30 min in-class presentation on a selected NES technology. The rawmaterials for the preparation of the in-class presentations are made available to the students. Evaluated are presentation aspects like:quality of the content and the coverage, presentation organization and style, capability to answer follow-up questions as part of the in-classdiscussion (see "advocate" role below).

IV: "Advocate" role and in-class discussions: After each presentation there is a short in-class discussion under the guidance of a studentthat is named as "advocate" for this particular talk. Attendance and active participation in the discussion (with comments, questions, etc.) isexpected from all students. Like the main presenter, the "advocate" has to familiarize himself with the raw materials for the presentationand should be capable of asking critical follow-up questions and to guide the in-class discussion with the help of the docent.

IV: In-class quiz: After the completion of a cluster of in-class presentations in a given topical area, the students take part in a short ~15 minwritten quiz that checks the level of acquired knowledge from the in-class presentations and the follow-up discussions

IV: Final written test: After the completion of all in-class presentations, the students take part in a ~45 min final test that checks the overalllevel of acquired knowledge from the in-class presentations and the follow-up discussions.

IV: Project assignment: Organized in small teams (3-4 persons), the students are asked to design, develop and demonstrate a relativelysimple but complete NES application that involves data acquisition, processing and communication, thus gaining hands-on experience inworking with state-of-the-art NES hardware and software. Evaluated are: two "project milestone presentations" (intermediate and finalpresentation) using the same criteria as for the "in-class presentations", a "project demo" (general functionality, achievement of designgoals, effective use of HW and SW) and a "final project review" (team work, code quality, documentation, effective use of version controltools). Students are also asked to self-evaluate the relative contribution of each team member as part of the team, which is considered inthe formation of the final individual marks for the project assignment.

Test elements Categorie Points Duration/ExtentIV Project demo (Deliverable assessment) practical 8 30 minIV 2 Project milestone presentations, 6 points each(Deliverable assessment)

oral 12 2x 30 min

IV In-class presentation assignment (Deliverableassessment)

oral 20 30 min

IV "Advocate" role, attendance and in-class discussions(Learning process review)

oral 4 30 min

IV 2 In-class quizzes, 5 points each (Examination) written 10 2x 15 minIV Final project review (Deliverable assessment) practical 10 30 minIV Final written test (Examination) written 36 45 min


Learning Outcomes The main objective of this module is to improve the technical knowledge in the area of communication networks, and in particular, studentswill gain a deeper understanding of specific technologies and their characteristics (basic functionality, adjustments to user requirements,etc.). Students will have the opportunity to broaden their knowledge of specific communication technologies (UMTS/LTE, Internet,multimedia, ad-hoc, sensor networks, etc.). This course will also provide a possibility to improve the knowledge of the overlapping areas ofmany different communication technologies that will be discussed from different perspectives (wireless communication, high-speednetworks). Additionally, during the seminars students will have the opportunity to elaborate on the chosen technology or technology-orientedproblem and discuss it in front of a bigger audience. This will help to develop practical presentation skills as well as critical thinking.

Requirements for participation and examination Desirable prerequisites for participation in the courses: BSc Module „Kommunikationsnetze“ or similar knowledge.


Module completion

Network Technologies (Medium)

Module title:

Network Technologies (Medium)

Credits:

9

Responsible person:

Zubow, Anatolij

Office:

FT 5

Contact person:

Zubow, Anatolij

Website:

http://www.tkn.tu-berlin.de/?108248#ktechm

Display language:

Englisch

E-mail address:

[email protected]




Test description:In total 100 Portfolio points can be obtained:* Seminar (34 Portfolio points),* Two lectures out of: VL Modern Wireless Networks, VL High-speed Network Technologies, VL Ad-hoc- and Sensor Networks or IVContent Delivery Techniques (each lecture or IV 33 Portfolio points)

* VL Modern Wireless Networks - written test (Examination) 33 Points - < 90 min* VL High-speed Network Technologies - oral consultation (Examination) 33 Points - 30min* VL Ad-hoc and Sensor Networks - final lecture written test (Examination) 33 Points - < 90 min* IV Content Delivery Techniques - oral exam 23 Points, Kategorie mündlich, 30 Minuten* IV Content Delivery Techniques - project results 10 Points, Kategorie praktisch, 30h ongoing


Test elements Categorie Weight Duration/ExtentSM Network Technologies - presentation (Examination) oral 10 20 minSEM Network Technologies - written report anddocumentation (Deliverable assessment)

written 19 about 10-12 pages

SM Network Technologies - attendance and discussion(Learning process review)


Two lectures: each lecture or IV 33 Portfolio points flexible 66 siehePrüfungsformbeschreibung


Learning Outcomes The main objective of this module is to improve the technical knowledge in the area of communication networks, and in particular, studentswill gain a deeper understanding of specific technologies and their characteristics (basic functionality, adjustments to user requirements,etc.). Students will have the opportunity to broaden their knowledge of specific communication technologies (UMTS/LTE, Internet,multimedia, ad-hoc, sensor networks, etc.). This course will also provide a possibility to improve the knowledge of the overlapping areas ofmany different communication technologies that will be discussed from different perspectives (wireless communication, high-speednetworks). Additionally, during the seminars students will have the opportunity to elaborate on the chosen technology or technology-orientedproblem and discuss it in front of a bigger audience. This will help to develop practical presentation skills as well as critical thinking.

Requirements for participation and examination Desirable prerequisites for participation in the courses: BSc Module „Kommunikationsnetze“ or similar knowledge is required.


Module completion

Network Technologies (Small)

Module title:

Network Technologies (Small)

Credits:

6

Responsible person:

Zubow, Anatolij

Office:

FT 5

Contact person:

Zubow, Anatolij

Website:

http://www.tkn.tu-berlin.de/?108248#ktechs

Display language:

Englisch

E-mail address:

[email protected]




Test description:In total 100 Portfolio points can be obtained:* Seminar (50 Portfolio points),* One lecture out of: VL Modern Wireless Networks, VL High-speed Network Technologies, VL Ad-hoc- and Sensor Networks or IVContent Delivery Techniques (each lecture 50 Portfolio points).

* VL Modern Wireless Networks - written test (Examination) 50 Points - < 90 min* VL High-speed Network Technologies - oral consultation (Examination) 50 Points - 30min* VL Ad-hoc and Sensor Networks - final lecture written test (Examination) 50 Points - < 90 min* IV Content Delivery Techniques - oral exam 35 Points, Kategorie mündlich, 30 Minuten* IV Content Delivery Techniques - project results 15 Points, Kategorie praktisch, 30h ongoing


Test elements Categorie Weight Duration/ExtentSEM Network Technologies - written report anddocumentation (Deliverable assessment)

written 28 about 10-12 pages

SEM Network Technologies - attendance and discussion(Learning process review)


SEM Network Technologies - presentation (Examination) oral 15 20 minOne lecture. each lecture 50 Portfolio points flexible 50 siehe

Prüfungsformbeschreibung


Lernergebnisse After successful completion of the project the students are capable of solving small tasks on their own. This includes background research,documentation and management of the project.

Voraussetzungen für die Teilnahme / Prüfung Wünschenswerte Voraussetzungen für die Teilnahme an den Lehrveranstaltungen: Knowledge of the compulsory modules of Bachelor studies and the Master module “Network architectures - basics” is mandatory.Desirable: good English language skills.



Network Architectures - Master Project (small)

Titel des Moduls:

Network Architectures - Master Project (small)

Netzwerkarchitekturen - Master-Projekt (klein)

Leistungspunkte:

6



Sekretariat:

MAR 4-4

Ansprechpartner:

Enghardt, Theresa

Webseite:


Anzeigesprache:

Deutsch

E-Mailadresse:

[email protected]





Prüfungselemente Kategorie Punkte Dauer/Umfangpractical part including the report praktisch 70 6 Monatepresentation mündlich 30 30 Min


Learning Outcomes On successful completion, students will be able to: - apply the approach of parameterized complexity analysis to solve computationally hard (NP-hard) problems- design and analyze parameterized algorithms- identify practically relevant and tractable special cases of problems that are computationally hard in general- use complexity-theoretic methods to determine the limits of parameterized algorithmics

Requirements for participation and examination Desirable prerequisites for participation in the courses: Basic knowledge on algorithms


Module completion

Parameterized Algorithmics

Module title:

Parameterized Algorithmics

Credits:

6

Responsible person:

Niedermeier, Rolf

Office:

TEL 5-1

Contact person:

Thielcke, Christlinde

Website:

http://www.akt.tu-berlin.de/menue/teaching

Display language:

Englisch

E-mail address:

[email protected]



Learning Outcomes The course deals with mathematic-physical modelling of a sensor by using the photographic camera as example. The modelling iscompletely expressed by algebraic projective geometry. Not only studying object reconstruction using image data of a multifaceted sensor,but and first of all the complete modelling of technically relevant issues in a homogeneous mathematical framework is important in thiscourse. This framework is also used for 3D-computer graphics. Interdisciplinary application of the contents are demonstrated using variousillustrative examples from e.g. manufacturing industries to geography, medicine and social sciences.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Modul 20363 (Lineare Algebra für Ingenieurwissenschaften)


Module completion

Photogrammetric Computer Vision

Module title:

Photogrammetric Computer Vision

Credits:

6

Responsible person:

Hellwich, Olaf

Office:

MAR 6-5

Contact person:

Dennert, Marion

Website:

http://www.cv.tu-berlin.de/

Display language:

Englisch

E-mail address:

[email protected]

Grading: Type of exam: Language: Duration/Extent:graded Written exam English 90 minutes


Learning Outcomes Students gain practical experience in dealing with modern communication systems, their design, evaluation and implementation. The focusis put primarily on modern systems of wireless mobile communications, as well as Internet protocols and applications. Skills obtained in thismodule will enable students to design, implement and evaluate modern communication systems. Thanks to working in small teams,graduates also develop project management and team working skills.

Requirements for participation and examination Desirable prerequisites for participation in the courses: The contents of the BSc module „Kommunikationsnetze” or at least "Rechnernetze und Verteilte Systeme ("Computer Networks andDistributed Systems") is essential. Students should consider choosing only projects for which the required expertise of software and/ordevelopment tools had been previously acquired. The individual requirements are dependent on the project and can be found in the detailed project description at the following website:http://www.tkn.tu-berlin.de/menue/tknteaching/studentenprojekte/parameter/en/


Module completion

Project in advanced network technologies

Module title:

Project in advanced network technologies

Credits:

6

Responsible person:

Zubow, Anatolij

Office:

FT 5

Contact person:

Zehl, Sven

Website:

http://www.tkn.tu-berlin.de/menue/tknteaching/studentenprojekte/parameter/en/

Display language:

Englisch

E-mail address:

[email protected]





The mark will take into account creativity, project management, presentations, as well as the actual implementation and evaluation of theproposed solution. The project needs to be documented with a final report and a survey page in the Internet.

Test elements Categorie Points Duration/Extent(Deliverable assessment) Survey page written 10 one A4 page(Learning process review) Self organization of work &solution quality


(Learning process review) 3 Milestone presentations (10points each)

oral 30 3x1h

(Deliverable assessment) Final report written 20 ~20-30 pages


Lernergebnisse Students are able to work on complex questions in the field of statistical methods in ai and ml and present the results properly.The abilities involve: working with literature, precision of specified questions, planning, execution and evaluation of scientific work,presentation and discussion of obtains results.

Voraussetzungen für die Teilnahme / Prüfung Wünschenswerte Voraussetzungen für die Teilnahme an den Lehrveranstaltungen: ---



Projects in Machine Learning and Artificial Intelligence

Titel des Moduls:

Projects in Machine Learning and Artificial Intelligence

Projekte im Maschinellen Lernen und Künstlicher Intelligenz

Leistungspunkte:

9


Opper, Manfred

Sekretariat:

MAR 4-2

Ansprechpartner:

Ruttor, Andreas

Webseite:

http://www.ki.tu-berlin.de/menue/lehre

Anzeigesprache:

Deutsch

E-Mailadresse:

[email protected]




Prüfungsbeschreibung:Die Gesamtnote gemäß § 47 (2) AllgStuPO wird nach dem Notenschlüssel 2 der Fakultät IV ermittelt.

Prüfungselemente Kategorie Punkte Dauer/Umfang(Ergebnisprüfung) Projektbericht schriftlich 60 3 Std.(Ergebnisprüfung) Seminarvortrag mündlich 40 45 Minuten


Learning Outcomes Graduates of this module are able to master methods and techniques with which the quality of embedded systems can be systematicallyensured, in particular computer-aided verification and test automation techniques. They have knowledge about existing techniques andknow how to apply them.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Knowledge from bachelor modules in Computer Science/Technical Computer Science or the like. Recommended are basic skills in softwareengineering for embedded systems.


Module completion

Quality Assurance of Embedded Systems

Module title:

Quality Assurance of Embedded Systems

Credits:

6

Responsible person:

Glesner, Sabine

Office:

TEL 12-4

Contact person:

Herber, Paula

Website:

No information

Display language:

Englisch

E-mail address:

[email protected]

1.) [PES] 2 bestandene Tests

Grading: Type of exam: Language: Duration/Extent:graded Oral exam English 20 - 30 min


Learning Outcomes After completion participants will have acquired the necessary knowledge and skills to read, discuss, understand, present, and summarizeoriginal research in the field of computer architecture and follow original research talks. They are able to provide feedback on each other’swork and to formulate research questions. They are further able to write a review paper about recent developments in computerarchitecture.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Module Advanced Computer Architecture or a similar course


Module completion

Recent Advances in Computer Architecture

Module title:

Recent Advances in Computer Architecture

Credits:

3

Responsible person:

Juurlink, Bernardus

Office:

EN 12

Contact person:

Juurlink, Bernardus

Website:


Display language:

Englisch

E-mail address:

[email protected]

Grading: Type of exam: Language:graded Portfolio examination English


Test description:Grading system 2 will be used:

95% or more1.090% or more1.385% or more1.780% or more2.075% or more2.370% or more2.765% or more3.060% or more3.355% or more3.750% or more4.0Less than 50%5.0

Test elements Categorie Duration/Extent(Deliverable assessment) Presentation practical 50 20 min(Deliverable assessment) Written review written 50 jeweils 2 Wochen


Learning Outcomes Graduates of this module are able to understand current research papers in the field of embedded systems, software engineering,verification and/or testing and to present their results.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Knowledge from bachelor modules in Computer Science/Technical Computer Science/Software Engineering or the like.


Module completion

Seminar Software and Embedded Systems Engineering

Module title:

Seminar Software and Embedded Systems Engineering

Credits:

3

Responsible person:

Glesner, Sabine

Office:

TEL 12-4

Contact person:

Berg, Nils Erik

Website:

http://www.sese.tu-berlin.de/menue/studium_und_lehre/

Display language:

Englisch

E-mail address:

[email protected]




Test description:The students have to prepare a written report of 6-9 pages and a presentation. They also have to write reviews of reports of otherstudents. Students also have to contribute to the Question & Answer session of the talks of other participants.

According to § 47 (2) AllgStuPO the final mark is calculated using the grading key 2 of school IV.

Test elements Categorie Points Duration/ExtentReviews written 10 2 pReport written 45 6 -9 pPresentation oral 45 45 min


Learning Outcomes This is a Master Degree module on special topics in the area of Communications Network Security and Autonomous Security. Aftercompletion of this module students will have deep understanding of:-state of the art security problems and solutions for communications networks,-security needs of future systems, communications networks and Internet The seminar will enable students to analyse and understand security needs of future communications networks. Students will be able tofollow state of the art research results published in high rank conferances and journals. Module will cover the topics which are not only inthe interest of research institutes and academies but also industries.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Basic understanding in:- Computer Communications Networks and Operating Systems- Network Security and Cryptography- Algorithms


Module completion

Special Topics in Communications Networks and Autonomous Security

Module title:

Special Topics in Communications Networks and Autonomous Security

Credits:

3

Responsible person:

Albayrak, Sahin

Office:

TEL 14

Contact person:

Bsufka, Karsten

Website:

http://www.aot.tu-berlin.de/index.php?id=2662

Display language:

Englisch

E-mail address:

[email protected]




Test description:Die Gesamtnote gemäß § 47 (2) AllgStuPO wird nach dem Notenschlüssel 2 der Fakultät IV ermittelt.

Test elements Categorie Points Duration/Extent(Ergebnisprüfung) Presention: Slides written 10 20 slides(Ergebnisprüfung) Seminar text written 50 10 - 30 pages(Ergebnisprüfung) Presentation: Content practical 30 40 minutes(Ergebnisprüfung) Presentation: Talk oral 10 40 minutes


Learning Outcomes The students gain:- Understanding of the most important principels of acoustical human-computer interaction.- Basic knowledge of the production, transmission and perception of speech signals.- Basic knowledge of the transmission and coding of speech and audio signals- Basic knowledge of speech-technological systems (speech recognition, speech synthesis, spoken dialogue systems)- Practical experience in the design of acoustical human-computer interfaces.- Presentation and knowledge transfer skills

Requirements for participation and examination Desirable prerequisites for participation in the courses: Mandatory: NoneDesirable: Basic knowledge of signal processing.


Module completion

Speech Signal Processing and Speech Technology

Module title:

Speech Signal Processing and Speech Technology

Credits:

6

Responsible person:

Möller, Sebastian

Office:

TEL 18

Contact person:

Hirsch, Tobias

Website:


Display language:

Englisch

E-mail address:

[email protected]




Test description:Schriftliche Tests: Es werden zwei schriftliche Leistungsstandüberprüfungen durchgeführt (je 40min). Die erste Überprüfung wird etwa denLernstand zur Hälfte des Semester abfragen und die zweite den Lernstand am Ende des Semesters.

Hausaufgaben: Es wird die Fähigkeit überprüft erlerntes Wissen anhand von konkreten Programmieraufgaben anzuwenden. Diese werdenzweimalig im Semester als einzureichende Hausaufgabe abgefragt.

Demonstration eines Sprachdialogsystems: Zum Ende des Kurses wird ein Projekt durchgeführt, welches die Studierenden selbstständigerarbeiten und präsentieren

Test elements Categorie Points Duration/Extent(Ergebnisprüfung) 2 Hausaufgaben à 10 Punkte written 20 6 Programmieraufgaben als

Zweiergruppe(Lernprozessevaluation) Demonstration einesSprachdialogsystems

practical 10 10-15 min als Gruppe

(Punktuelle Leistungsabfrage) Schriftlicher Test 1 written 35 40 Minuten(Punktuelle Leistungsabfrage) Schriftlicher Test 2 written 35 40 Minuten


Lernergebnisse Students gain- Knowledge in working on specific State-of-the-Art topics in the field of Usability.- Measurement of quality and usability of interactive Systems.- Practical experience in technical realization of human-machine interfaces.- Knowledge of the design and implementation cycle of interactive systems.- Practical proving of the knowledge in quality and usability judgement on selected technical systems.- Presentation of project work.




Study Project Quality & Usability (6 CP)

Titel des Moduls:


Studienprojekt Quality & Usability (6 LP)

Leistungspunkte:

6


Möller, Sebastian

Sekretariat:

TEL 18

Ansprechpartner:

Hirsch, Tobias

Webseite:

http://www.qu.tu-berlin.de/menue/studium_und_lehre/modulkatalog/

Anzeigesprache:

Deutsch/Englisch

E-Mailadresse:

[email protected]





Präsentation: Die im Projekt erstellten Inhalte werden vorgestellt und erläutert. Die Richtigkeit des Inhalts und der Stil des Vortrags, sowiedie Vollständigkeit der Resultate werden bewertet.

Projektbericht: Der Projektbericht beschreibt detailiert die erzielten Resultate und den Lösungsansatz. Weiterhin stellt er die verwendetenVorarbeiten (Literatur, Softwarebibliotheken etc.) vor. Gegebenfalls enthält der Bericht die Dokumentation zur weiteren Nutzung derResultate (z.B. bei Softwareprojekten).

Prüfungselemente Kategorie Punkte Dauer/Umfang(Deliverable assessment) Presentation mündlich 20 15-30 min(Deliverable assessment) Project Results schriftlich 80 30-40 Seiten als Gruppe


Lernergebnisse Students gain- Knowledge in working on specific State-of-the-Art topics in the field of Usability.- Measurement of quality and usability of interactive Systems.- Practical experience in technical realization of human-machine interfaces.- Knowledge of the design and implementation cycle of interactive systems.- Practical proving of the knowledge in quality and usability judgement on selected technical systems.- Presentation of project work.





Titel des Moduls:


Studienprojekt Quality & Usability (9 LP)

Leistungspunkte:

9


Möller, Sebastian

Sekretariat:

TEL 18

Ansprechpartner:

Hirsch, Tobias

Webseite:


Anzeigesprache:

Deutsch/Englisch

E-Mailadresse:

[email protected]




Prüfungsbeschreibung:Präsentation: Die im Projekt erstellten Inhalte werden vorgestellt und erläutert. Die Richtigkeit des Inhalts und der Stil des Vortrags, sowiedie Vollständigkeit der Resultate werden bewertet.

Projektbericht: Der Projektbericht beschreibt detailiert die erzielten Resultate und den Lösungsansatz. Weiterhin stellt er die verwendetenVorarbeiten (Literatur, Softwarebibliotheken etc.) vor. Gegebenfalls enthält der Bericht die Dokumentation zur weiteren Nutzung derResultate (z.B. bei Softwareprojekten).

Prüfungselemente Kategorie Punkte Dauer/Umfang(Deliverable assessment) Presentation mündlich 20 30 min(Deliverable assessment) Project Results schriftlich 80 50-60 Seiten als Gruppe


Learning Outcomes Students have hands-on experience with all aspects of project work (including team-based software development, project management,collaborative decision making, documenting and communicating project results) in the area of cloud systems. They are able to solve real-world problems in the context of the design and evaluation of cloud- and web-based service oriented application systems in enterprise andIoT contexts.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Knowledge on programming with Java, distributed systems and middleware concepts. Prior experience with LaTeX. Willingness to workwith new technologies, architectural paradigms, and programming models.


Module completion

Cloud Prototyping

Module title:

Cloud Prototyping

Credits:

12

Responsible person:

Tai, Stefan

Office:

EN 14

Contact person:

Tai, Stefan

Website:


Display language:

Englisch

E-mail address:

[email protected]




Test description:Insgesamt können 100 Portfoliopunkte erreicht werden. Die Gesamtnote gemäß §47 (2) AllgStuPO wird nach dem Notenschlüssel 2 derFakultät IV ermittelt.

Test elements Categorie Points Duration/Extent(Ergebnisprüfung) Mündliche Rücksprache oral 30 30 MIn.(Ergebnisprüfung) Ergebnispräsentation practical 20 ca. 20h(Ergebnisprüfung) Dokumentation practical 20 ca. 60h(Ergebnisprüfung) Entwickelte Softwareartefakte practical 30 ca. 160h


Learning Outcomes Graduates of this module are endued with competences in the following areas: services, protocols, and elements of infrastructures withinclassical wired and mobile circuit-switched telecommunication networks, 5th Generation Mobile Networks and Software-based networks.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Knowledge of technologies in the area of wired and wireless communication networks is required (e.g. “Telekommunikationsnetze”).


Module completion

5th Generation Mobile Networks

Module title:

5th Generation Mobile Networks

Credits:

6

Responsible person:

Magedanz, Thomas

Office:

MAR 5-5

Contact person:

Pauls, Michael

Website:

http://av.tu-berlin.de/teaching

Display language:

Englisch

E-mail address:

[email protected]



Learning Outcomes Graduates of this module are endued with competences in architectures, protocols, and technologies for connectivity, communication,(semantic) data exchange and (Edge-based) virtualization used within Industrial Internet of Things (IIoT) use cases. They will further beabIe to identify and systematically solve prospective challenges of future IloT developments and applications.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Knowledge about architectures, protocols, and technologies used within distributed systems and semantic information modelling.


Module completion

Industrial Internet of Things (IIoT)

Module title:

Industrial Internet of Things (IIoT)

Credits:

6

Responsible person:

Magedanz, Thomas

Office:

MAR 5-5

Contact person:

Willner, Alexander

Website:


Display language:

Englisch

E-mail address:

[email protected]



Lernergebnisse The major goal of this seminar is the intensive discussion of current questions in the field of 5G and the Industrial Internet of Things.Graduates of this module are endued with competences regarding current research activities, research results and trends in the context ofclassic telecommunication systems, Software-based networks and the Internet of Things. Furthermore, the seminar teaches the studentsmethodical competences to do literature research and presentations in a scientific environment independently.

Voraussetzungen für die Teilnahme / Prüfung Wünschenswerte Voraussetzungen für die Teilnahme an den Lehrveranstaltungen: Kenntnisse von Architekturen, Protokollen und Technologien verteilter Systeme.



5G and IIoT Seminar

Titel des Moduls:

5G and IIoT Seminar

Leistungspunkte:

3


Magedanz, Thomas

Sekretariat:

MAR 5-5

Ansprechpartner:

Pauls, Michael

Webseite:

Keine Angabe

Anzeigesprache:

Deutsch

E-Mailadresse:

[email protected]





Prüfungselemente Kategorie Punkte Dauer/UmfangPresentation of seminar paper mündlich 50 15 minWritten paper schriftlich 50 ~10 pages


Lernergebnisse Graduates of this module are endued with competences in the following areas: services, protocols, and elements of infrastructures withinclassical wired and mobile circuit-switched telecommunication networks, Software-based networks or the Internet of Things. Furthermore,they learn to use this knowledge in practice and have the ability to accomplish development tasks in small groups, to document theprocedures, and to present the results. They can independently perform the necessary literature research and develop own concepts.

Voraussetzungen für die Teilnahme / Prüfung Wünschenswerte Voraussetzungen für die Teilnahme an den Lehrveranstaltungen: Kenntnisse von Architekturen, Protokollen und Technologien verteilter Systeme.



5G and IIoT Project

Titel des Moduls:

5G and IIoT Project

Leistungspunkte:

9


Magedanz, Thomas

Sekretariat:

MAR 5-5

Ansprechpartner:

Pauls, Michael

Webseite:


Anzeigesprache:

Deutsch

E-Mailadresse:

[email protected]





Prüfungselemente Kategorie Punkte Dauer/UmfangPresentation of concept and work plan mündlich 10 15 minPresentation of intermediate work mündlich 10 15 minPresentation and demonstration of project outcome mündlich 10 15 minImplementation work praktisch 30 depends on topicEvaluation flexibel 20 depends on topicWritten report (documentation) schriftlich 20 ~15 pages



Requirements for participation and examination Desirable prerequisites for participation in the courses: Siehe Studien- und Prüfungsordnung.


Module completion

Masterarbeit ICT Innovation StuPO 2016

Module title:

Masterarbeit ICT Innovation StuPO 2016

Master Thesis

Credits:

30

Responsible person:

Möller, Sebastian

Office:

No information

Contact person:

Möller, Sebastian

Website:

No information

Display language:

Englisch

E-mail address:

[email protected]

Grading: Type of exam: Language: Duration/Extent:graded Thesis English No information



Learning Outcomes Aim:Students passing this curriculum will have a good understanding of standardisation, network effects and platform strategies and theireconomic impact on the microlevel of companies as well as the macrolevel of the national, European and global innovation landscape. Description:This series of introductory lectures will deal with standards, dominant designs and platforms covering examples from different industries e.g.ICT. The holistic perspective of this course covers findings from the field of innovation economics, platform management and appliedstandardisation research. It integrates practical knowledge about harmonization, standardisation and network economics into a coherentcurriculum which platform strategies build on. Context:From an economics and business perspective, standardisation can act as an innovation catalyst by facilitating knowledge transfer andtechnology diffusion in the market. Standards and platforms are elements of the technical infrastructure of our society. They facilitate theexchange of goods, services and information. Standards provide users with a common terminology or accepted aspects of measuring andtesting*. Standards function as a platform for new innovations to flourish and for an infrastructure to be formed. Platforms use standardisedinterfaces to build a network of compatible products to gain a large installed base and increase switching costs. Industries defined byplatform technologies, commonly see a single dominant platform emerge as an industry wide de-facto standard because the managementof platforms is especially vulnerable to factors like network externalities.A successful example is the mobile telephone, which rapid diffusion in Europe benefited from the timely release of the GSM standard. As afurther example, laser technology, for which the German industry achieved a leading position both in Europe and worldwide via earlystandardisation can be mentioned. The introduction of a common charging plug for electric cars is yet another example, and will likelyfacilitate the development of a wide spread charging station infrastructure. * Some of these standards we are aware of like standardised paper sizes, standards in the www, plugs and sockets of electronicequipment, bolts matching nuts etc.. Other standards we may not be aware of like standards for the height of steps on a flight of stairs orstandards for the safety of playground equipment

Requirements for participation and examination Desirable prerequisites for participation in the courses: Preferable: Basic skills in accordance with Business and Economics courses


Module completion

Standardisation and Plattform Management

Module title:

Standardisation and Plattform Management

Credits:

6

Responsible person:

Blind, Knut

Office:

No information

Contact person:

Essoun, Brigitte

Website:

http://www.inno.tu-berlin.de

Display language:

Englisch

E-mail address:

[email protected]




Test description:The portfolio examination consists of the following elements, adding up to a maximum of 100 credits. The grading follows the jointconversion key of the School of Economics and Management (decision of the school's council dated May 28, 2014 - FKR VII-4/8-28.05.2014).

Test elements Categorie Points Duration/ExtentLecture (written exam) written 70 85Exercise (guest lectures, assignment) written 30 flexibel


Learning Outcomes - The ability to successfully apply the learned knowledge for development of a new product or business concept- The ability to systematically explore and create ideas or modify existing business ideas for answering market needs- The ability to systematically explore obstacles in building a viable business concept based on a technology- An in-depth understanding of the different phases of a business development process- The ability to transform new ideas into business solutions for a commercial market environment, combined with decision-making andleadership competencies- The ability to work in multi-disciplinary teams- The ability to present a concept to an internal audience as well as to an external panel of financiers- The ability to reflect upon ethical and team processes.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Exclusively for students studying MSc ICT Innovation


Module completion

Venture Campus - ICT Innovation

Module title:

Venture Campus - ICT Innovation

Credits:

9

Responsible person:

Kratzer, Jan

Office:

H 76

Contact person:

Perner, Susanne

Website:

http://www.entrepreneurship.tu-berlin.de/menue/masterprogramme_qualifizierung/courses/venture_campus/

Display language:

Englisch

E-mail address:

[email protected]




Test description:Die Portfolioprüfung besteht aus den folgenden Elementen, in denen in der Summe maximal 100 Punkte erreicht werden können. DieBenotung erfolgt nach dem gemeinsamen Notenschlüssel der Fakultät VII (Beschluss des Fakultätsrates vom 28.05.2014 - FKR VII-4/8-28.05.2014)./The portfolio examination consists of the following elements, adding up to a maximum of 100 credits. The grading follows the jointconversion key of the School of Economics and Management (decision of the school's council dated May 28, 2014 - FKR VII-4/8-28.05.2014).

Test elements Categorie Points Duration/ExtentEvaluation of Business Plan Presentation oral 50 20 Minuten pro TeamEvaluation of written Business Plan written 50 25 Seiten/pages (excl. App)

pro Team


Learning Outcomes •Understanding innovation management as a corporate task defining and managing the corporate innovation system•Being able to identify relevant managerial aspects for improving innovation initiative at the corporate level, understanding organizationdesign for initiatives and how this affects the corporate innovation portfolio.•Identifying relevant parameters of the management of innovation collaborations, understanding the opportunities for extending thecorporate resource and capability base for innovation by collaborating with external partners, and understanding the advantages ofmanaging partners in an innovation network.•Aligning corporate innovation strategy, including alliance strategy and activities, with an effective corporate IPR position and being able todelineate an adequate IPR strategy.•Explaining the effects of services becoming a more integral or even dominant part of corporate offerings on innovation management•Understanding the informal side of the corporate innovation organization and its effects on innovation team activities. Being able to identifyand influence relevant parameters of an innovation enhancing organizational culture.•Appreciating the opportunities of new technologies (e.g., IoT, additive manufacturing, DLT) for innovations, identifying the specificchallenges for innovation management and being able to discuss the opportunities for leveraging such technologies in the context ofinnovation management.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Module 70202 (Organisation und Innovationsmanagement) passed


Module completion

Innovation Management - Corporate Innovation

Module title:

Innovation Management - Corporate Innovation

Credits:

6

Responsible person:

Salomo, Sören

Office:

H 71

Contact person:

Salomo, Sören

Website:

http://www.tim.tu-berlin.de

Display language:

Englisch

E-mail address:

[email protected]





Test elements Categorie Points Duration/ExtentExam written 50 60 min.Group presentation practical 30 40 min.Group seminar essay practical 20 5 pages


Learning Outcomes In the I&E Study students will apply their I&E-knowledge to a an practically relevant challenge/question. After completion of the I&E Study module, students…… have the ability to apply, synthesize, and evaluate prior I&E learning within a specific innovation or entrepreneurial project setting and aspecific innovation area.… have the ability to choose and apply relevant concepts/methods due to their challenge.… have the ability to produce a professional writing on a business analysis topic.… have the ability to apply concepts, methods and tools and evaluate them critically.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Participation in M. Sc. ICT Innovation


Module completion

I&E Study

Module title:

I&E Study

Credits:

6

Responsible person:

Kratzer, Jan

Office:

H 76

Contact person:

Middermann, Laura Helen

Website:

http://www.entrepreneurship.tu-berlin.de

Display language:

Englisch

E-mail address:

[email protected]

Grading: Type of exam: Language: Duration/Extent:graded Written exam English No information


Learning Outcomes The ability to innovate ensures the competitiveness of high-income countries and its enterprises. At the same time innovations question theclassical economic equilibrium models. The course intends to shed light on different typologies of innovations, also considering multiple methodologies of empirical research ininnovation economics. The second part of the course deals with different explanatory approaches of innovation economics: amongst othersneo-classical, evolutionary and historic-institutional ones. The course studies both theoretical models and their empirical application, changing between micro and macro-economic perspectives.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Basic skills have to be in accordance to all A-Business and A-Economics courses and, if necessary, have to be certificated.


Module completion

Innovation Economics

Module title:

Innovation Economics

Credits:

6

Responsible person:

Blind, Knut

Office:

MAR 2-5

Contact person:

Essoun, Brigitte

Website:


Display language:

Englisch

E-mail address:

[email protected]





Test elements Categorie Points Duration/ExtentLecture - exam written 60 60 minExercise - essay written 40 20 pages


Learning Outcomes -In depth understanding of the general process and roles involved in developing an idea and starting up a new technology-based company-The ability to systematically explore customers and markets-In depth understanding and the ability to systematically explore business organization and projects-In depth understanding and the ability to systematically explore basic product and process development-In depth understanding and the ability to systematically explore basic entrepreneurial finance-In depth understanding and the ability to systematically explore the important elements in managing companies and developing its humanresources

Requirements for participation and examination Desirable prerequisites for participation in the courses: There are no prerequisites for the participation in this module.


Module completion

Innovation Management & Entrepreneurship Basics

Module title:

Innovation Management & Entrepreneurship Basics

Credits:

6

Responsible person:

Kratzer, Jan

Office:

H 76

Contact person:

Middermann, Laura Helen

Website:

http://www.entrepreneurship.tu-berlin.de

Display language:

Englisch

E-mail address:

[email protected]





Test elements Categorie Points Duration/ExtentPresentation/Essay flexible 40 No informationWritten Test flexible 60 No information


Learning Outcomes The course participants have knowledge of the principal concepts and key principles of the marketing of innovative products and services.They are able to recall strategies, methods and specific instruments that can ensure market-oriented innovation processes. Graduates of the course are able to describe different types of innovation and are able to derive marketing implications. Furthermore,participants are able to describe how to select the appropriate target market, how to position the innovation relative to other solutions, howto communicate its benefits, set effective prices and select appropriate distribution channels, and how to develop solid relationships andalliances.

Requirements for participation and examination Desirable prerequisites for participation in the courses: There are no prerequisites for the participation in this module.


Module completion

Innovation Marketing

Module title:

Innovation Marketing

Credits:

6

Responsible person:

Klasse-Talke, Katrin

Office:

H 95

Contact person:

Klasse-Talke, Katrin

Website:

http://www.marketing.tu-berlin.de

Display language:

Englisch

E-mail address:

[email protected]

1.) Module Marketing und Produktionsmanagement (#70183) passed





Test elements Categorie Points Duration/ExtentExam written 50 60 minPresentation/Report written 50 10-20 Seiten/Folien


Learning Outcomes Based on the lecture Innovation Economics this course puts the focus on Innovation Policy aspects. In a first step, various economicjustifications for government involvement in innovation activities will be presented with a focus on market and system failure aspects. In a second step, the development of Innovation Policy initiatives at National, European and International level will be presented andanalyzed. The course provides a general understanding of government´s Innovation Policy as well as knowledge about specific InnovationPolicy programs. Students learn to understand developments in Innovation Policy and to discuss them critically. The general analytical abilities for PublicPolicy Management (instrument design, implementation and evaluation) are taught in an appropriate way. The contextual understanding ofinnovation policy also makes it possible to incorporate government regulation in business considerations.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Basic skills have to be in accordance to all A-Business and A-Economics courses. Basic knowledge of economics and businessadministration is required to be able to reasonably follow the course. It is recommended to visit the course “Innovation Economics”beforehand.


Module completion

Innovation Policy

Module title:

Innovation Policy

Credits:

6

Responsible person:

Blind, Knut

Office:

No information

Contact person:

Essoun, Brigitte

Website:


Display language:

Englisch

E-mail address:

[email protected]





Test elements Categorie Points Duration/ExtentExercise (guest lectures, homework assignments) flexible 30 flexibelLecture (written test) written 70 85 min


Learning Outcomes The course is intended to give the students a broad overview concerning the exploitation and protection of intellectual assets and to conveythe basic principles of Intellectual Property (IP) Management. Relevant topics are means of formal protection (patents, brands, copyrightaspects, utility models etc.) as well as means of informal protection of IP assets (secrecy, technical solutions etc.). Furthermore, the coursecovers the fields of protection strategies and alternative ways of appropriation and enforcement of intellectual property, referring to researchco-operations, knowledge transfer processes and markets of technology. In addition, current topics and problems with respect to legalsystems display another field, potential scenarios of this system will be presented and solution approaches suggested. Selected guestlectures provide a high practical relevance. As part of the exercise a workshop held by industry partners supplements the theoretical and empirical knowledge from the lecture. Duringthe workshop the students will analyze and solve realistic case studies. Alternatively, the students may participate in a seminar where theydiscuss and illustrate the topics of the lectures with the help of current events. Students learn to recognize differences between the methods and instruments of intellectual property protection while critically weighingtheir pros and cons. It is taught in an appropriate way to transfer economic models into practical management use. Thus it is possible, forexample, to assess which methods and instruments may be combined for creating a reasonable business strategy.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Basic skills have to be in accordance to all A-Business and A-Economics courses. Basic knowledge of economics and businessadministration is required to be able to reasonably follow the course. It is recommended to visit other courses at our chair “InnovationEconomics”, “Innovation Policy” and “Strategic Standardisation”. When in doubt students may contact the respective teachers of the IPmanagement course.


Module completion

Intellectual Property Management

Module title:

Intellectual Property Management

Credits:

6

Responsible person:

Blind, Knut

Office:

MAR 2-5

Contact person:

Essoun, Brigitte

Website:

http://www.inno.tu-berlin.de.

Display language:

Englisch

E-mail address:

[email protected]





Test elements Categorie Points Duration/ExtentLecture (written test) written 38 60 minMultiple-choice tests flexible 12 flexibleExercise (case study, presentations, final report) flexible 50 flexible


Learning Outcomes The course analyzes the influence of Open Source and Peer Production from an economic, political and societal point of view. In particular,it will deal with the potential conflict between Open Innovation and traditional formal protective rights, the motivation and organization ofOpen Source communities, and the economic impact of Open Source. The participants will learn about the implications of using and contributing to Open Source projects in enterprises. The course will enablethem to assess and evaluate the use of Open Source products, and develop strategies for cooperation and collaboration with Open Sourcecommunities.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Basic Knowledge of lectures in Innovation Economics and IP Management.


Module completion

Open Source and IP in the Digital Society

Module title:

Open Source and IP in the Digital Society

Credits:

6

Responsible person:

Blind, Knut

Office:

No information

Contact person:

Essoun, Brigitte

Website:

http://www.inno.tu-berlin.de.

Display language:

Englisch

E-mail address:

[email protected]





Test elements Categorie Points Duration/ExtentWritten report written 50 flexibelPresentation oral 50 flexibel


Learning Outcomes After participating in this course, students should be in a position to:(1) understand and critically reflect upon key concepts and theories in strategic innovation management(2) understand and critically discuss conceptual and empirical research papers on strategic innovation management,(3) analyze and develop adequate solutions to some of the practical challenges of strategic innovation management, and(4) apply important tools in strategic innovation management intelligently based on a thorough understanding of their respective strengthsand weaknesses.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Human Side of InnovationModul 70202 (Organisation und Innovationsmanagement) Bestanden


Module completion

Strategic Innovation Management

Module title:

Strategic Innovation Management

Credits:

6

Responsible person:

Kleer, Robin

Office:

H 71

Contact person:

Kleer, Robin

Website:

http://www.tim.tu-berlin.de

Display language:

Englisch

E-mail address:

[email protected]





Test elements Categorie Points Duration/ExtentExam written 50 60 min.Group seminar essay practical 20 5 pagesGroup presentation practical 30 40 min.


Learning Outcomes The objective of this module is to instruct students in approaches of industry analysis and current problems of top management ofcorporations. The students shall learn how to handle these instruments themselves and how they can learn from this analysis for their futurework career. With the support of industry experts, the students are taught to present professional case studies and how to stand theirground in an English discussion. Furthermore, the students should learn how to derive solutions for strategic problems, and thus how tomanage the challenges with which modern management has to deal.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Previous participation in our bachelor module „Grundlagen des Strategischen und Internationalen Management“ or comparable courses


Module completion

Strategic Management

Module title:

Strategic Management

Credits:

6

Responsible person:

Knyphausen-Aufseß, Dodo

Office:

H 92

Contact person:

Wendland, Maren

Website:

http://www.strategie.tu-berlin.de

Display language:

Englisch

E-mail address:

[email protected]

Grading: Type of exam: Language:graded Portfolio examination English

Grading scale:No grading scale given...


Test elements Categorie Duration/ExtentWritten test in the "SMOC" course 35 No informationWritten test in the "CSCO" course 35 No informationCase study 30 No information


Learning Outcomes Digital technologies are continuously evolving. They affect people, organizations, industries and society. The basic premise of this course isthat digital technologies are rapidly transforming not only the way how we live and work, but also how companies are organized andinnovate, and the fundamental nature of a wide range of industries. Therefore entrepreneurs, managers, policy makers and technologyexperts need to understand the business implications, technology paradigms, changing customer needs and management practices ofinnovations in digital-centric businesses. The goal of this course is to provide a deeper understanding of key concepts of digital innovation.Students will learn how to conceive, lead and execute digital innovation initiatives. Students will become acquainted with the main concepts and perspectives of digital innovations. They will understand the nature andimpact of digital transformation and hence will be empowered to become digital innovators, who drive effective digital innovation initiatives inorganizations.

Requirements for participation and examination Desirable prerequisites for participation in the courses: Basic skills have to be in accordance to all basic compulsory courses in Business Administration and Economics.


Module completion

Digital Innovation

Module title:

Digital Innovation

Credits:

6

Responsible person:

Blind, Knut

Office:

MAR 2-5

Contact person:

Essoun, Brigitte

Website:


Display language:

Englisch

E-mail address:

[email protected]





Test elements Categorie Points Duration/ExtentExam (on lecture) written 70 85 min.Presentation (in excercise) oral 30 30 min.


Msc ICT Innovation StuPO 2017 - tu-berlin.de · Um diesen Studiengangsbereich zu bestehen, müssen...

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