Prospective Students

Goals/professional fields

...and what can you do with it later?

The primary aim of the consecutive Master's degree programme in Computer Science at the TU Braunschweig is to deepen the basic knowledge and skills acquired in the Bachelor's degree programme and to enable students to carry out scientific work. This includes a systematic method-oriented approach, precise analysis, specification, modelling and prototype implementation. Students are enabled to work independently and autonomously on more complex computer science issues in a wide range of application areas.

The Master's degree programme in Computer Science at the Technische Universität Braunschweig is characterised by a strong scientific focus.

After successfully completing the Master's degree programme in Computer Science, graduates...

• are able to perform a demanding job as a computer scientist, in a specialist or managerial position.
• have advanced knowledge of computer science.
• can develop and analyse sophisticated algorithms independently.
• can think analytically, recognise complex relationships, assess existing solutions and develop their own solutions to complex problems.
• are able to present their results appropriately.
• can work successfully in a group and communicate efficiently with different target groups.
• are able to work independently in an academic capacity and carry out research activities.

The Computer Science Master's programme can also be studied part-time...

The Computer Science degree programme can also be studied part-time if there is a special reason (e.g. caring for underage children or gainful employment)

Please note, however, that part-time study is not designed to be part-time! This means that courses are offered during daytime throughout the week.

The standard period of study is doubled for part-time study programmes. Only 30 CP (instead of 60 CP in a full-time programme) may then be acquired per academic year or a maximum of 16 CP instead of 30 CP per semester.

The application for part-time study must always be submitted for two consecutive semesters or a complete academic year in advance and must be submitted to the Enrolment Office of the TU Braunschweig by 1 October for students starting in the winter semester and by 1 April for students starting in the summer semester.

The application must be accompanied by an individual application form, agreed upon by the chairperson of the examination board or the person nominated by the subjects and confirmed in writing by signature.

If you have any questions, please contact the Computer Science programme coordinator, Yvonne Dietze (Rebenring 58a, room 124, telephone: 0531/391 2843).

A total of 120 credit points (CP) must be earned in the Master's degree programme in Computer Science.

These are distributed across the following areas:

• Compulsory elective area Computer Science (80 to 82 credit points or 62 to 68 credit points if a minor subject is chosen), including:
  • One compulsory seminar, 5 CP
  • One project work, 15 CP (optional)
• Minor subject, 14 to 18 CP (optional)
• Elective area Mathematics and Key Qualifications, 8 to 10 CP
• Master's thesis, 30 CP (completion time: 6 months)

[You can read more about the programme structure here.]

If you take closely related modules totalling 70 CP (including Master's thesis, project work and seminar), a field of study (specialization) can be recognised!

Application for a place on the programme

The Master's degree programme is admission-free with special admission requirements (see admission regulations). You can apply here from 1 June to 15 July for the winter semester and from 1 December to 15 January for the summer semester at TU Braunschweig.

According to the admission regulations § 2 para. (1), basic knowledge in the central subjects of computer science must be demonstrated at the time of application (at least 60 LP), which can be understood as follows:

• Algorithms and Data Structures
  (concept of algorithms, graphs, searching in graphs, correctness and complexity of algorithms, data structures, sorting, recursion, hashing)
• Programming
  (Basics of imperative and object-oriented programming using the Java language, recursive methods, reliability of programming, programming of dynamic and recursive data structures, basics of parallel programming, basics of graphics programming)
• Logic
  (propositional logic, predicate logic, Boolean algebra, normal forms)
• Computer Engineering
  (Hardware structure of a computer system, number representation, number arithmetic, switching networks, minimisation, standard switching networks, switching systems, realisations, buses (basic functions and protocols), processor structure (microarchitecture), instruction set architecture, basics of assembly language)
• Theoretical Computer Science
  (Finite automata, regular languages, basement automata, context-free grammars and languages, Turing machines, Chomsky hierarchy, computability and decidability, complexity, NP-completeness)
• Software Engineering
  (Overview of software techniques, procedures, design, implementation, object orientation, modelling, UML, software/system architectures, patterns in software development)
• Software Development
  (Development of complex software systems: capturing a task with models, realisation in a design and implementation)
• Operating Systems
  (History of operating systems, process management, inter-process communication, memory management, input and output, file systems)
• Computer Networks
  (Historical classification, overview of networks and protocols, layer models and layers, protocol mechanisms, brief introduction to Internet protocols)
• Database Systems
  (the relational data model, ER and UML modelling, relational calculi and algebra, structure and use of the Structured Query Language SQL, basics of database administration, triggers and active databases, normalisation of databases)

Furthermore, basic knowledge in the central subjects of mathematics must be demonstrated to the extent of at least 15 CP, which can be understood as follows:

• Analysis
  (limits, convergence, continuity, differential calculus in one and more variables, integral calculus in one and more variables, Taylor expansion, elementary functions, curve discussion, simple examples of ordinary differential equations, initial value problems, Fourier expansion, extrema with constraints, integral theorems of Gauss and Stokes)
• Linear Algebra
  (Linear systems of equations, Gauss algorithm, vector and matrix calculus, real and complex vector spaces, spaces with inner product, analytic geometry, eigenvalues and eigenvectors, diagonalisability, important types of linear mappings and their matrix representations, normal forms and matrix decompositions, best approximation (method of least squares, motions)
• Discrete Mathematics
  (Combinatorial proof principles, counting methods, permutations, combinations, variations, inclusion-exclusion, asymptotic analysis, graphs, trees, important graph properties, modular arithmetic, applications in cryptography)