- Degree
- Master of Science
- Course location
- Cottbus
- Teaching language
- • English
- Languages
- The programme is designed to be completed entirely in English. It is possible, however, to take additional mandatory elective classes in German if one wishes.
- Full-time / part-time
- • full-time
- Programme duration
- 4 semesters
- Beginning
- Winter and summer semester
- Additional information on beginning, duration and mode of study
- The semester begins in April for the summer semester and in October for the winter semester.
- Application deadline
- • Applicants with foreign qualifications for admission to higher education: 15 July for the following winter semester and 15 January for the following summer semester
• Applicants with European Union/European Economic Area citizenship: 15 August for the following winter semester and 15 February for the following summer semester
• Applicants with German qualifications for admission to higher education: 31 August for the following winter semester and 1 March for the following summer semester
Please be sure to check https://www.b-tu.de/en/artificial-intelligence-ms/admission (https://www.b-tu.de/en/artificial-intelligence-ms/admission) for updates and further details.
- Tuition fees per semester in EUR
- None
- Combined Master's degree / PhD programme
- No
- Joint degree / double degree programme
- No
- Description/content
- If you want to understand and design the algorithms that underlie artificial intelligence, the international Artificial Intelligence MSc programme is the right place for you. This programme is focused on mastering fundamental research knowledge and techniques which will allow you to learn to develop future AI methods.
Through a combination of current knowledge and modern methods from computer science, psychology, and mathematics, you will be able to research and design complex artificial intelligence procedures. Such methods are, for example, Deep Learning, Support Vector Machines, Markov Random Fields, Wavelets, Bayesian Networks, optimal reasoning, knowledge representation, pattern recognition, multi-scale representation, programme verification, or constraint-based programming. You learn to conceptualise AI methods, to test their special properties, to validate them, to develop them further and to implement them in a targeted manner.
This degree programme places a core focus on understanding and explaining the mathematical and algorithmic models that underlie artificial intelligence; therefore, it demands a solid background on theoretical computer science. Furthermore, the behaviour of AI procedure should be predictable and describable. The degree programme puts emphasise on students learning to understand how the system will react in unexpected circumstances but also encourage trusting the system. Of course, you will also learn to asses and critically question the limits and implications of applying artificial intelligence to socially relevant problems.
An increasing number of companies and research institutions are ensuring their future development by looking for specialists with innovative and creative design skills in the field of artificial intelligence. Many of our cooperation partners, such as the Lausitz Center for Artificial Intelligence (LZKI), the Leibniz Institute for High Performance Microelectronics (IHP), the German Aerospace Center (DLR), Fraunhofer Institutes, or Rolls Royce offer opportunities to work on research projects during your studies or to write your Master's thesis there.
If you are more interested in building and further developing complex hardware- or software-based systems of AI, we recommend the Master's programme Artificial Intelligence Engineering (https://www.b-tu.de/en/kuenstliche-intelligenz-technologie-ms) (taught in German).
The courses in the international degree programme Artificial Intelligence, MSc are taught in English.
Professional Fields of Activity
• Data Science
• Mathematical data analysis
• Medical data analysis
• Development of algorithms and methods of Artificial Intelligence, e.g. machine learning
• Mathematical and scientific treatment of questions concerning artificial intelligence
• Autonomous driving and assistance systems
• Intelligent control systems, for example supply chains or energy and environmental sectors
• Collaboration in universities and research departments