All Data Science students have been invited for a welcome event on October 14, 2019. In the event, we provided an overview of the course program, introduced some of the faculty, and the student representatives of the department.
All necessary information can be found on the following slides:
Whoever (from the accepted students) received no e-mail with an invitaion to SLACK, please send a remark to Nina Eißner.
The most important document you should know, including an overview of modules and their respective ECTS can be found here:
Discipline-Specific Admission Regulations for the Master’s Program in Data Science at the University of Potsdam.
Please read this document (and possibly existing recent amendments - see here ).
Each semester this document is created but unfortunately not provided in English language. Nevertheless, you can find an overview of courses in this PDF:
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.
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.
The course "Data Science" is held each winter term by Dr. Evdokimov.
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.
The course "Bayesian Inference and Data Assimilation" is held each summer term (Prof. Reich).
The course "Intelligent Data Analysis" is held each summer term by Prof. Scheffer.
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.
Many courses offered in the Computer Science department can be booked under this module. For instance,
Also check out the offerings of the Digital Engineering Faculty.
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.
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.
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.
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.
In order to do an external internship, you have to find:
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.
In order to inform your supervisors, please find an overview of the scope for the research module and internship beow. It is extracted from our module catalog. Unfortunately, this is only provided in German language in the moment.
Unfortunately the registration is only provided in German language in the moment. The respective webpage can be found here: Register Master Thesis Uni Potsdam.
Once you found a supervisor and a topic please fill out the form below ASAP. Andreas Schwill needs to sign it and in between one week it should arrive at the Central Examination Office.
Minimum writing period is 2 month (plus one week of registration duration via Central Examination Office).
If you have an external supervisor, please ask your external supervisor to state shortly your topic and the scope to the internal Uni Potsdam supervisor. (Similar to Research Project or Internship).
Please find the respective Documents here:
(Be aware that this is not a validated translation only an orientation. Legally binding language remains German language. If doubts remain please contact Examination Office.)
Most courses use Moodle to distribute teaching materials and announcements. Please register for the courses that you want to take.
With your university account you will be able to explore current Job positions in University, well known research institutes or in industry. Job postings include student jobs (WerkstudentIn/Hilfswissenschafliche Mitarbeit), internships or positions with finished degree.
You are eager to learn more?! But you cannot squeeze it into your semester load?
Here you can find the online courses offered by the HPI: