Foto: Matthias Friel
The content is taught with the help of appropriate video lectures as they can be found, e.g., on Coursera, Stanford Online or MIT OpenCourseWare.
The meetings in presence are used for discussing questions and tasks.
oral exam, 20-30 minutes
Algorithms and Data Structures: Growth of functions and O-notation; Divide and conquer; Dynamic Programming; Sorting and searching; Elementary data structures; Elementary algorithms on graphs
Formal Languages: Regular languages and finite automata; Context-free languages and pushdown automata; Recursively enumerable languages and Turing maschines
Theoretical Foundations: Decidability and computability; halting problem; Non-determinism; complexity classes P and NP; Rekursion; Inductive definitions
Master Students in Cognitive Systems or Data Science with bridging module in CS
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