New Master's degree programs at FIDS

With us, computer science is written in many colors! Because computer science is one thing above all: highly versatile. For us, core computer science is just as much a part of it as the many different fields of application in which your skills are needed!

In the Master's degree programm in Computer Science, you can deepen or expand your knowledge of advanced topics in core computer science and - if you wish - specialize in specific application areas.

The program is divided into

•     a compulsory area (incl. Master's thesis) (min. 60 LP)
•     the compulsory elective area “Core Computer Science” (at least 18 CP)
•     the compulsory elective area “Specialization” (at least 42 CP)

Not to be missed: The compulsory area

Advanced knowledge of software engineering and algorithms is essential for us when studying Computer Science. You will acquire this knowledge in two lectures of the same name with associated labs (6 CP each). An elective module allows you to complete courses in Computer and Data Science according to your own interests (12 CP). The compulsory area is completed by a seminar on current topics in Computer Science (6 CP) and the Master's thesis module (30 CP).

It all comes down to the core: The Core Computer Science elective area

You must choose three modules (at least 18 CP) from 20 planned modules in the areas of Theoretical Computer Science, Computer Engineering, Practical Computer Science and Applied Computer Science. Examples of modules are Topics in Theoretical Computer Science, Modern Machine Learning, Advanced Explainable AI, Embedded Systems, Advanced Data Engineering, Digital Image Processing - AI-based Approaches, Post-Quantum Cryptography etc.

Whatever you want: The Specialization elective area

You can (but do not have to) specialize in one of four specializations as part of your studies by completing modules amounting to at least 42 CP from one specialization (according to specified regulations). You can choose between the specializations:

•     Core Computer Science
•     Bioinformatics
•     Human-Centred Computing
•     Information Systems

In all specializations, there is a compulsory elective area, so that you can also choose modules within a specialization according to your interests. If you complete your Master's thesis project as part of your specialization, we will highlight your specialization on your Master's certificate.

It's up to you: Our admission procedure

If you want to study the M.Sc. Computer Science at the University of Regensburg, you should have

• a Bachelor's degree with a final grade of 2.5 or better (or at least 138 LP in your current Bachelor's degree with a provisional final grade of 2.5 or better) - if you have not already studied Computer Science or Data Science in your Bachelor's degree, but are burning with interest in Computer Science, you can be admitted if you meet the other requirements;
• successfully completed credits from the field of  Computer Science amounting to 60 CP and from the field of Mathematics amounting to 18 CP (from a total of 30 LP from Computer Science and Mathematics you can be admitted with conditions);
• proof of English at level C1 CEFR or a Bachelor's thesis written in English;
• international applicants must also prove their subject knowledge by passing a Graduate Record Examination (GRE) General Test.

Further details on the requirements as well as further information on the admission procedure, deadlines and necessary documents will be available here soon.

Data scientist, AI expert, data engineer, data analyst - you can be all of these with your degree from the Master's degree program in Data Science. In addition, all doors are open to you in application fields of data science, such as biomedical research, the technology industry, business or other future-oriented fields. Your M.Sc. in Data Science will prepare you to develop innovative solutions for complex problems and to work in an interdisciplinary field. During your studies, you can deepen or expand your knowledge in advanced topics of statistics and machine learning and specialize in specific areas of application.

The degree program is divided into

•     a compulsory area (incl. Master's thesis) (min. 66 LP)
•     the compulsory elective area “Machine Learning and Statistics” (min. 12 CP)
•     the compulsory elective area “Specialization” (at least 42 CP)

Not to be missed: The compulsory area

Advanced knowledge of current trends in deep learning and reinforcement learning is essential for us when studying data science. You will acquire this at the beginning of your studies in the lecture “Modern Machine Learning” with associated lab (6 CP). Two elective modules allow you to complete courses from Computer and Data Science or from other subject areas according to your own interests (12 CP each). The compulsory area is completed by a seminar on current topics in data science (6 CP) and the Master's thesis module (30 CP).

It all comes down to the core: The compulsory Machine Learning and Statistics elective area

You choose modules worth at least 12 CP from 11 planned modules, all of which are dedicated to central topics in data science and machine learning. Examples of modules are: Statistical Machine Learning, Advanced Statistics I and II, Advanced Explainable AI, Advanced Data Engineering, Digital Image Processing - AI-based approaches etc.

Whatever you want: The Specialization elective area

You can choose from four specializations during your studies. You must choose one of these as a specialization by completing modules amounting to at least 42 CP from the specialization (according to specified regulations). You can choose between the specializations

•     Machine Learning and Statistics
•     Computational Life Sciences
•     Human-Centred Data Science
•     Information Systems

In all specializations, there is a compulsory elective area, so that you can also choose modules within a specialization according to your interests. If you complete your Master's thesis project as part of your specialization, we will highlight your specialization on your Master's certificate.

It's up to you: Our admission procedure

If you want to study the M.Sc. Data Science at the University of Regensburg, you should have

•  a Bachelor's degree with a final grade of 2.5 or better (or at least 138 CP in your current Bachelor's degree with a provisional final grade of 2.5 or better) - if you have not already studied Data Science or Computer Science in your Bachelor's degree, but are burning with interest in Data Science, you can be admitted if you fulfill the other requirements;
• successfully completed credits from the field of Data Science amounting to 30 CP and from the field of Mathematics amounting to 18 CP (from a total of 30 LP from Data Science and Mathematics you can be admitted with conditions);
• proof of English at level C1 CEFR or a Bachelor's thesis written in English;
• international applicants must also prove their subject knowledge by passing a Graduate Record Examination (GRE) General Test.

Further details on the requirements as well as further information on the admission procedure, deadlines and necessary documents will be available here soon.

Developing AI systems while keeping humans in mind - that is the core topic of human-centered artificial intelligence. Such applications range from search engines and the automatic recognition of hate comments using natural language processing to personalized dialogue systems. Your studies in the M.Sc. Human-Centred Artficial Intelligence will prepare you to develop, implement and test solutions for Human-Centred AI. We provide you with the necessary advanced technical know-how in the field of computer science and data science as well as the necessary knowledge in the field of human-computer interaction and psychology!

The degree program is divided into 14 compulsory modules (incl. Master's thesis) with a total of 120 CP. Within many of the compulsory modules, you have thematic options and can organize your studies according to your interests!

Not to be missed: The Core

In addition to an introductory module that gives you an overview of the entire field of human-centered AI, you will complete five core modules during your studies: In AI Ethics you will discuss ethical dilemmas in AI systems, in Technologies for Human-Centred AI 1 and 2 you will develop solutions for (AI) systems by applying human-centered design principles, e.g. in the field of Natural Language Programming, Recommender Systems and Information Retrieval, and in the Free Elective module you can deepen your knowledge of topics or gain insights into new topics and trends - also in the field of Computer Science and Data Science.

What you want: The Specialization

We provide you with a framework of topics and you can choose which topics interest you the most. This is the core idea of our specialization area, in which you complete seven modules and within the modules you can choose between different courses and projects from Information Science, Computer Science, Data Science and Psychology, among others. The seven modules include: Explainable AI, Generative AI, Information Behavior, Deep Reinforcement Learning, Current Topics in Human-Centred AI, Empirical Human-Centred AI and Computational Human-Centred AI.

What you can: The (Final) Project

Towards the end of your studies, you can apply all your knowledge and skills in a project seminar by planning and implementing a project in the field of human-centered AI independently and as part of a team. If you wish, this project can result in your Master's thesis.

It's up to you: Our admission procedure

If you also want to study the M.Sc. Human-Centred AI at the University of Regensburg, you should have

• a Bachelor's degree with a final grade of 2.5 or better (or at least 138 LP in your current Bachelor's degree with a provisional final grade of 2.5 or better) - it is not primarily important in which subject you have completed your Bachelor's degree, but above all that you fulfill the subject requirements listed below;

• successfully completed credits in the field of Information Science, i.e. in the field of natural language processing and information retrieval with at least 18 CP, in the field of empirical and statistical research with at least 12 CP and in the field of programming with 12 CP (from a total of 30 CP you can be admitted with conditions);

• proof of English at level C1 CEFR or a Bachelor's thesis written in English;

• International applicants must also prove their subject knowledge by taking a Graduate Record Examination (GRE) General Test.

The M.Sc. in Human-Centred AI can always be started in the winter semester. Further details on the requirements as well as further information on the admission procedure, deadlines and necessary documents will be available here soon.