At the end of the course the student is able to:

• use and explain elementary data structures like lists, heaps, binary trees, and priority queues
• use and explain elementary algorithms like sorting, traversing and updating data structures, and basic optimization problems
• analyse the time complexity of algorithms and operations on data structures, e.g. using the Master Theorem or recursions, and use dynamic programming
• use and understand the Euclidean algorithm, the “grand daddy of all algorithms” (Knuth), in particular its computational efficiency, and its relevance in applications such as, e.g., RSA public key encryption
• use, explain and design algorithms on graphs and networks, such as computation of shortest paths, spanning trees, maximum flows, stable matching and clustering problems
• solve second-order linear recurrence relations using characteristic polynomials or generating functions