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Module Elective courses 1, Bachelor Course Media Computer Science (ER 3)
Module summary

Elective courses 1

MKIB5503

Prof. Dr.-Ing. Holger Vogelsang

4 ECTS points / 4 Contact hours

5th Semester

none

none

The student should be able to lay his emphasis on individual interests.

Individual exams
Course Affective Computing

I W924

Lecture

Prof. Thomas Hinz
M.Sc. Bernd Dudzik

German

2/2

Homework 1 Semester (graded)

Emotional expressions are important signals for people to make sense of situations, actions and relationships in their social interactions with each other. Is the empowerment of technological systrms with the capacity to also sense and express emotions able to improve their users’ interactions with them? This question is the driving force behind the field of Affective Computing.

The students know different theories of emotions, contrast them with each other and debate them. They apply the acquired knowledge by addressing problems from within the primary areas of application for Affective Computing through the development of  prototypical interactive systems that are capable of sensing or expressing emotions.

Lecture notes, case studies.

Course App Programming

I W912

Lecture

M.Sc. Adrian Wörle

German

2/2

Written Exam 90 Min. (graded)

The lecture teaches the construction of mobile media applications. The main concepts are discussed using the Android platform. In a first partt, the basic technologies and limitations of mobile devices are shown. The second part examins different development strategies like native applications, device independend abstractions and web applications. A main part of the lecture is the integration of different media types into mobile applications and the constraints the developer has to keep in mind.

will be announced

Leacture with exercise

Course Big Data Engineering

I W926

Lecture

Prof. Dr. Christian Zirpins

German

2/2

Written Exam 90 Min. (graded)

The lecture Big Data Engineering addresses the systematic construction of data-intensive systems. Generic architectural approaches are introduced in order to design robust, performant and scalable data systems for various applications. For different architectural areas various kinds of data storage and processing models are discussed. Topics include, among others, distributed file systems, serialization, batch and stream processing with MapReduce and other programming models, queuing mechanisms and NoSQL databases. These are both conceptually described as well as implemented by means of exemplary tools and techniques. The focus is on established industry standards such as Apache Thrift, Hadoop, Kafka, Cassandra, Storm. These are illustrated by means of an exemplary Web Analytics application.

 

During the course students acquire, among others, the following abilities:

  • They evaluate different approaches of data systems for given application problems with specific requirements.
  • They describe structure and function of specific architectural approaches for Big Data systems.
  • They categorize tools and techniques for Big Data systems and utilize them professionally.
  • They design architecture and data models as well as processing logic and queries for given Big Data applications and implement these based on specific open source tools and techniques.

  • Nathan Marz, James Warren, "Big Data: Principles and best practices of scalable realtime data systems", Manning, 2015, ISBN: 1-617290-34-3
  • Martin Kleppmann, "Designing Data-Intensive Applications", O'Reilly, 2014 (Early Release), ISBN: 978-1-4493-7332-0
  • Tom White, "Hadoop: the definitive guide: storage and analysis at internet scale", 4. ed., O'Reilly, 2015, ISBN: 978-1-491-90163-2    
  • Michael Frampton, "Big Data Made Easy: A Working Guide to the Complete Hadoop Toolset", Apress, 2015, ISBN: 978-148-420-094-0
  • Vivek Mishra, "Beginning Apache Cassandra Development", Apress, 2014, ISBN: 978-148-420-142-8
  • Additional literature will be announced during the lecture

Independent work relates to the preparation and followup of lectures, laboratory exercises and exam preparation.

Course Business Intelligence

I W179

Lecture

Prof. Dr. Uwe Haneke

German

2/2

Written Exam 90 Min. (graded)

Students can apply the theoretical concepts developed during the lecture by working on case studies and the possibility to evaluate different software tools.
  • Introduction and business-management background
  • The concept of data warehousing
  • Business Analytics and Balanced Scorecard (BSC)
  • CRM and Data Mining
  • Trends in Business Intelligence-Case studies

PowerPoint slides, exercise-sheets, continuative information on the web-site and in the ILIAS-eLearning-system, access to different BI-tools via VMware server and the SAP competence center. Bauer, A., Günzel, H. (Hrsg.) (2004): Data Warehouse-Systeme - Architektur, Entwicklung, Anwendung. dpunkt.Verlag, Heidelberg.

Lecture combined with exercise sessions and case studies
Course Cloud Computing

I W913

Lecture

Dipl. Inform. (FH) Michael Fischer
Dipl. Inform. (FH) Georg Magschok

German

2/2

Written Exam 90 Min. (graded)

The buzzword "Cloud" represents a variety of interesting technologies which gained importance in the life of a computer science professional. Those are being collected, examined, explained and understood during the course. Primary objective is usefulness for the student, regardless of whether he acts as a cloud user, developer, administrator or even entrepreneur. Understand the broad meaning of "Cloud Computing" from a variety of perspectives: Definition, use cases, technology basics, key players, APIs, scaling, redundancy …

Powerpoint slides

Course Computer Vision Laboratory

I W773

Laboratory

Prof. Dr.-Ing. Astrid Laubenheimer

German

2/2

Laboratory Work 1 Semester (graded)

Prior registration or agreement with a lecturer required

Course Digital Transformation & digital marketing

I W929

Lecture

Marc Steinmetz
Prof. Thomas Hinz

German

2/2

Homework 1 Semester (graded)

Course Empatically pragmatic

I Wxxx

Lecture

Prof. Thomas Hinz
Dipl.Design. Heike Biscosi

German

2/2

Verbal Exam/Concept 20 Min. (graded)

Course ERP Systems with Laboratory

I W551

Lecture

Prof. Dr. rer. pol. Mathias Philipp

German

4/4

Written Exam 90 Min. (graded)

Contents:
ERP basics, system integration, system architectures, and logistics: Distribution (SD), Materials Management (MM), Production Planning and Control (PP) as well as Financial Accounting (FI) and Controlling (CO). In addition, an overview is given to the software selection.

Recommended reading: Lecture material completely as PowerPoint documents, blackboard notes for interactive development of central problem positions, a main textbook to ERP, a main textbook to SAP ECC 6.0.

Kind of work: Lecture participation

Course Game Programming

I W620

Lecture

Prof. Dr. Peter Henning

English

2/2

Written Exam 90 Min. (graded)

Course New Lecture

I W156

Lecture

Prof. Dr. Martin Sulzmann

English

2/2

Written Exam 90 Min. (graded)

Course New Lecture

I W501

Lecture

Prof. Dr. Frank Schaefer

German

2/2

Written/verbal Exam 90/20 Min. (graded)

Course New Lecture

I W502

Lecture

Prof. Dr. Thomas Morgenstern

German

2/2

Presentation 20 Min. (graded)

Course Parallel Systems

I W391

Lecture

Prof. Dr. Christian Langen

German

2/2

Written Exam 90 Min. (graded)

Course Video

I W925

Lecture

Marc Steinmetz
Prof. Thomas Hinz

German

2/2

Homework 1 Semester (graded)

Course „Empathic-pragmatic“. Methods in User Research.

I W503

Lecture

Dipl.Design. Heike Biscosi

German

2/2

Homework 1 Semester (graded)

User Research - methods all around fictitious and real users, to to establish a "human centered approach" in projects.

Teaching contents are methods which contribute to a better understanding of people and their usage contexts, to improve the development, design and evaluation of interactive products and systems.

Following topics - in theory and praxis - will be part of the seminar: 

  • Creative and qualitative research methods, such as target group analysis, mental models, persona design, persona-moodboard, job stories, cultural probes, user diaries, focus groups, interviews, scenarios and storyboards, user journeys, acceptance and usability testings.
  • Basic principles of different quantitative methods: survey and questionnaire design, descriptive statistics, laboratory-based studies, experimental studies.
  • Evaluation of quantitative methods, as described in research reports.

  • Lecture notes,
  • Case studies from practice,
  • further literature references will be given in the lecture.

Seminaristic lecture with practical exercises.

The list of electives offered in the current semester can be found in the News menu.