Dr Tugkan Batu

This course is available on the MSc in Applicable Mathematics, MSc in Operations Research & Analytics, MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (Research) and MSc in Statistics (Research). This course is available as an outside option to students on other programmes where regulations permit.

Students must have completed Algorithms and Computation (MA407) or have taken an equivalent course to provide a basic knowledge in analysis of algorithms: running time and correctness of an algorithm, basic knowledge in computer programming, preferably, in Java language, and should have experience with proofs and proof techniques used in pure mathematics.

Introduction to NP-completeness. Approximation Algorithms. Randomised Algorithms. Streaming Algorithms. Numerical Algorithms.

20 hours of lectures and 10 hours of seminars in the LT. 2 hours of lectures in the ST.

Weekly exercises are set and marked. Some of these will require implementation of programming exercises in Java.

T H Cormen, C E Leiserson, R L Rivest, and C Stein, Introduction to Algorithms; V Vazirani, Approximation Algorithms; R Motwani and P Raghavan, Randomized Algorithms.

Exam (75%, duration: 2 hours and 30 minutes) in the main exam period.
Coursework (25%) in the ST.