On top of the application orientation that is characteristic of the Technical University of Applied Sciences Würzburg-Schweinfurt (THWS), the focus of the Master’s programme in Artificial Intelligence lies equally on the methodological and scientific orientation. The focus is on a deep scientific understanding of AI techniques. Graduates of this programme are expected to work independently, critically and in a structured manner when solving problems and to be able to make intellectual transfers from existing knowledge to unfamiliar future problems.

Requirements to apply for the Master's programme in Artificial Intelligence at THWS:

Completed higher education degree of 210 ECTS and an overall grade of 2.5 or higher in the fields of Computer Science, Mathematics or a related field of study completed at a German higher education institution or equivalent. (With less ECTS, admission is possible under certain conditions.)

Furthermore:

1. From the Bachelor's programme, an applicant must have at least 20 ECTS credits in mathematics, which in particular provide sufficient knowledge in the areas of statistics/probability theory, (linear) algebra and calculus. The following list of topics is not complete, and should give a first idea: Real and Complex Numbers, Vectors and Vector Spaces, linear independence, basis and dimension, Matrices and Linear Algebra (arithmetic with matrices, trace and determinant, systems of linear equations, linear mappings, Eigenvalues and Eigenvectors), Calculus (sequences and series, limits of functions and continuity, differential and integral calculus in one variable, Taylor series), Advanced Linear Algebra (eigenvalue problems and their applications, matrix decomposition methods), Numerical Methods (interpolation methods, optimisation problems and algorithms), Probability Theory (basic concepts: events, Kolmogorov's probability, conditional probability and independence, discrete and continuous random variables, expected value and variance, key distributions: binomial, hyper-geometric, Poisson, exponential, normal, sums of random variables, central limit theorem), Inferential Statistics (point and interval estimates, significance tests).
   
   
2. From the Bachelor's programme, an applicant must have at least 15 ECTS credits in computer science, which provide sufficient knowledge in the areas of both practical computer science (typically demonstrated by courses in databases, operating systems, software engineering or distributed systems) and theoretical computer science (typically demonstrated by courses in algorithms and data structures, automaton theory, complexity theory or logic).
   
   
3. We expect good to very good grades in all these subjects relevant to the Master's programme, i.e. especially in mathematics and the theoretical and practical computer science subjects. This must be proven by submitting the Bachelor's programme transcript.
   
   
4. We expect application-oriented, advanced skills in programming (e.g., in Python), typically demonstrated by work samples from programming projects, internships or laboratories, providing access to public repositories would be good.
   
   
5. We want to see the applicant's Bachelor's thesis, which must deal with a scientific problem (if possible with the corresponding source code).