Introduction to the theory of approximation algorithms and complexity classes, examples include knapsack, bin packing, metric TSP, TSP in planar graphs, Euclidean TSP, Steiner trees; PCP-theorem, APX-reductions; LP relaxation.

The fundamental elements of imperative programming languages (variables, assignments,conditional statements, loops, procedures, pointers, recursion) are explained on the basis of C++.Simple data structures (lists, trees) and fundamental algorithms (searching, sorting)are discussed and implemented. Finally, the concept of object oriented programming is briefly explained.

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Presentation of recent publications in theoretical computer science, including results by diploma, masters and doctoral candidates.

Concepts to cope with: a) what can be accomplished in a fully automated fashion (algorithmically solvable) b) How to measure the inherent difficulty of tasks (problems) c) What is randomness and how can it be useful? d) What is nondeterminism and what role does it play in CS? e) How to represent infinite objects by finite automata and grammars?