Algorithms & Complexity
Algorithms are fundamental to computer science. They are the essence of computer programs and lie at the core of any software system. This course will cover fundamental techniques for designing efficient computer algorithms, proving their correctness, and analyzing their performance. It will also cover a variety of application problems that use these techniques. The contents include greedy algorithms, divide and conquer algorithms, dynamic programming, network flow, NP completeness and computational intractability, approximation algorithms, and randomized algorithms. Techniques on algorithm design and analyisis will be developed by drawing on problems from across many areas of computer science and related fields.
- Algorithm Design; J. Kleinberg and E. Tardos, Addison-Wesley 2005.
- Useful reference (not required): Introduction to Algorithms, (3rd Edition), by T. Cormen, C. Leiserson, R. Rivest, and C. Stein, McGraw Hill, 2009.
Master of Science in Financial Technology and Computing, Elective course, Lecture, 2nd year
Master of Science in Informatics, Foundation course, Lecture, 2nd year
Master of Science in Informatics, Foundation course, Lecture, 1st year
PhD programme of the Faculty of Informatics, Elective course, Lecture, 1st year (4 ECTS)
PhD programme of the Faculty of Informatics, Elective course, Lecture, 2nd year (4 ECTS)