Modules are containers that can be filled with courses; often, several alternative courses are linked to a module and can be selected. In order to take any course, you have to book the course under a module in the University of Potsdam's study-program management software PULS. In many cases, you can log into PULS and navigate to the node "Vorlesungsverzeichnis / Mathematisch-Naturwissenschaftliche Fakultät / Institut für Informatik und Computational Science / Master of Science / Data Science" to see which courses are available for each module. Note, however, that the list of courses available for each module in PULS is incomplete! Additional courses can be added on request.

Departments and Faculties

The Department of Computer Science, Department of Mathematics, Department of Business Information Systems, and other institutes contribute classes to the master program Data Science. Many classes of the Faculty of Science can be selected for the (advanced) applied data science modules. The Digital Engineering Faculty offers classes for the masters programs IT System Engineering and Data Engineering that can be selected for many modules. 

 It is worthwhile to browse the complete course catalog of these departments and faculties for courses that relate to the topic of a module but are not linked to the module in PULS. If the faculty member who is responsible for the module agrees that the course is a fit, then the course can be taken. To find out who holds responsibility for a chosen module please talk to the lecturer. The person responsible for the module has to verify your allowance in an e-mail to Wolfgang Severin and the course can be linked to a adequate module. This, however, is only possible in the first two weeks of each semester.

The following paragraphs provide additional detail information regarding some specific modules.

[INF-DS-C3] Data Science and Business Analytics

The course "Data Science" is held each winter term by Dr. Evdokimov.

[MAT-VMD837] Statistical Data Analysis

The course "Statistical Data Analysis" is held each winter semester. Students who have a background in mathematics should take this course in their first semester. Students who do not have a sufficient mathematical background should move this course to the third semester and should take the bridge module "Foundations of Stochastics" in the first semester instead.

[MAT-VMD838] Bayesian Inference and Data Assimilation 

The course "Bayesian Inference and Data Assimilation" is held each summer term (Prof. Reich).

[INF-DS-C1] Machine Learning

The course "Intelligent Data Analysis" is held each summer term by Prof. Scheffer.

[INF-DSAM1A/B] Advanced Machine Learning

• Intelligent Data Analysis II (each winter term, Prof. Scheffer)
• Machine Intelligence with Deep Learning (Dr. Yang, DEF)

[INF-DS-C4] Applied Data Science and [INF-CSAM6A/B] Advanced Applied Data Science

For this module, you can select any course at the University of Potsdam which deals with applications of data-science methods in any field. The course has to match your qualification state in that field. For example, courses in bioinformatics, geoscience, remote sensing, and computational linguistics can be suitable. When the faculty member of any course agrees that the course is suitable for you and Prof. Scheffer agrees that the topic falls into the broad category of applied data science, a link between this module and the course in question is created in PULS; this is only possible until October 31.

The following courses are recommended for this module.

• Ringvorlesung interdisziplinäre Mathematik: eine projektorientierte Einführung (Prof. Reich).
• Statistics for Stochastic Processes (Department of Mathematics)
• Ausgewählte Methoden und Techniken der Systembiologie und Informatik (Department of Biochemistry and Biology)
• Remote sensing of the environment (Department of Earth and Environmental Sciences)
• Bioinformatik biologischer Sequenzen / evolutionary genomics (Department of Biochemistry and Biology)

[INF-DS-C2] Data Infrastructures and Software Engineering and [INF-DSAM4A/B] Advanced Data Infrastructures and Software Engineering

Many courses offered in the Computer Science department can be booked under this module. For instance,

• Software Engineering I: only suitable for students who did not take a similar class in their Bachelor program (Prof. Hammer),
• Distributed Data Management (Prof. Naumann, DEF),
• Software Security (Prof. Hammer),
• Cluster Computing (Prof. Schnor),
• Principles of Databases and Knowledge-Based Systems (Prof. Schaub).

Also check out the offerings of the Digital Engineering Faculty.

[INF-DS-AM8A/B] Mathematical Foundations of Data Science

Most courses offered by the Department of Mathematics can be booked under this module. If a course is not listed under this module, ask the responsible faculty member for approval and ask Wolfgang Severin to create the link in PULS.

[INF-DSAM9] Computational Foundations of Data Science

Most courses offered by the Department of Computer Science can be booked under this module. If a course is not listed under this module, ask the responsible faculty member for approval and ask Wolfgang Severin to create the link in PULS.

[INF-DSRMA/B] Research Module A and Research Module B

We recommend that you complete your coursework, and then determine you have accumulated 78 or 75 credit points; the result depends on the number of 6 and 9 credit-point modules you booked. Choose the research module that lands you at 90 credit points; your master’s thesis will win you the final 30 points.

In order to find a research module, get an appointment with any collaborating faculty member at the University of Potsdam (see Departments and Faculty section as well as Institute of Geosciences, Biology/Biochemistry, Physics) whose course you enjoyed and who works on topics that you are interested in. Discuss possible topics and agree on how you will carry out your project under their supervision.  Generally one would hand in a report and give a presentation. Supplementary weekly attendance of seminars in research groups can also be required.

Quick guideline

1. Find a supervisor and topic. Ideally one professor from related departments or even better one in our own department. If you are unsure please email to study counsellor counsellorcs.uni-potsdamde or directly contact Examination Board schwillcs.uni-potsdamde.
2. Register ANY time throughout the semester for the Research Module A or B under YOUR SUPERVISOR. If you register for the wrong exam/supervisor you will risk to fail the course.
   In other words: the General PULS deadline mid November does not hold here.

It is possible to account for a research module if you are working on a research project in industry or external research institutions related to the field of Data Science.
Please find the adjusted guideline below.

1. Find a company or research institute and topic.
2. Find a supervisor at University of Potsdam. Ideally one professor from related departments or even better one in our own department. If you are unsure please email to study counsellor counsellorcs.uni-potsdamde or directly contact Examination Board schwillcs.uni-potsdamde.
3.  For confirmation it is necessary that the external supervisor sends an informal letter/e-mail with signature to the Uni Potsdam internal supervisor, stating briefly the research topic, aims and scope.
4. Register ANY time throughout the semester for the Research Module A or B under YOUR  INTERNAL SUPERVISOR. If you register for the wrong exam/supervisor you will risk to fail the course.
   In other words:  the General PULS deadline mid November does not hold here.

[INF-DSAM11] Applied Data Science Internship

In order to do an external internship, you have to find:

1. An organisation which will host your internship and let you work on a research project, and
2. A faculty member (any faculty member at the Detartments of Computer Science or Mathematics) who is willing to supervise your internship.

If your supervisor agrees to your internship project, register for the module in PULS. In your internship, you have to work on a suitable project and obtain results in some form. These results have to be documented in a written report and presented to your supervisor in a presentation. In order to be granted 12 ECTS your work should approximately cover 360 working hours (including preparation, actual work, report and presentation preparation).
It is possible to do an internship in another faculty of Uni Potsdam. In that case no faculty member at the Department of Computer Science or Mathematics is needed. Your supervisor will be the faculty member you work with.
Please find the guideline of the Research module for external superviors a little bit more up this page. It behaves the same with the Applied Data Science Internship.
Be aware, that Uni Potsdam allows you to partly reduce your semester fees if you are doing an external internhip. More information can be found here.

If you have any question, please contact the counsellor Henning Bordihn or program coordinator Nina Eißner.