Teaching
Students are in the focus of our teaching. We want to enable them to be able to understand the basic concepts, to learn acquiring knowledge independently and, as following, implement it adequately within a given context. Based on these requirements the content and didactic components of our teaching are established.
Our teaching offer is mainly based on the main research focus of the department in order to provide teaching grounded on recent academic developments. Qualifications in the area of big data analytics is a capability frequently asked for on the labor market. Current estimates for the US-American space reveal a lack of professionals and executives of 1.5 million people by the year 2018. German and European markets also report extensive demand of analytically educated professionals.
The second cornerstone of our teaching offer is centered on the central topics of Business Information Systems. This includes e.g. the definition of the IT-strategy, the assessment of information systems as well as modelling and the optimization of the operation processes. Respective courses provide the knowledge that is indispensable for the modern IT-characterized entrepreneurship. Moreover, they ensure the balanced combination of general and specified lectures.
The teaching offer should be of equal interest for diverse groups of students: Business Administration, Economics, Business Information Systems, Management and Economic Science. For this purpose, we aim to achieve the balance between the subject and methodological knowledge. Furthermore, this knowledge is accompanied with business practice case studies.
Bachelor's courses
Following courses are offered for bachelor students:
|
Modul |
Compulsory/ Non-compulsory |
Format |
Credit Points |
Term |
| Marketing und E-Business | Compulsory | Lecture + Tutorial |
4/6 StO/PO 2010(2/3) |
Winter |
| Strategie, Organisation und IT | Compulsory | Lecture + Tutorial | 4/6 | Summer |
|
Non-compulsory |
Seminar |
2 / 6 |
Summer |
|
|
Introduction to Python for Machine Learning & AI
|
Non-compulsory |
Lecture + Tutorial |
4 / 6 |
Winter |
|
Einführung in die Programmierung (Grundlagen der Programmierung) |
Non-compulsory | Lecture + Tutorial | 4 / 6 | Summer |
Writing a thesis
Requirements for writing a bachelor thesis:
Successful completion of the Seminar Wirtschaftsinformatik. Completion of the Business Intelligence Systems module before attending the seminar is recommended, but is not a prerequisite for writing a bachelor thesis
Master's Courses
For master students following courses are offered:
|
Modul |
Compulsory/Non-Compulsory |
Format |
Credit points |
Term |
|
| Business Analytics & Data Science (BADS) |
Non-compulsory (compulsory for master's WInfo) |
Lecture + Exercise Class | 4 / 6 | Fall | |
|
Non-compulsory Requirement: BADS |
Practical Seminar |
4 / 6 |
Spring |
||
| Advanced Data Analytics for Management Support (ADAMS) (neuronal networks, image/text) |
Non-compulsory Requirement: BADS |
Lecture + Tutorial | 4 / 6 | Spring | |
|
Non-compulsory Requirement: BADS |
Seminar |
2 / 6 |
Fall and Spring |
||
| Digital Marketing & Web Analytics |
Non-compulsory (not available at the moment) |
Lecture + Seminar | 4 / 6 | n/a | |
Writing a thesis
Requirements for writing a master thesis:
Successful completion of at least of one module of the Chair of Information Systems
- Applied Predictive Analytics or
- Seminar Information Systems
More information on bachelor's and master's theses can be found here: Theses
Current and interesting topics for theses can be found on Moodle
Frequently asked questions might already have been answered here: FAQ