Dr Tugkan Batu

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

The course is compulsory for students on the MSc Applicable Mathematics who are not taking MA421 Advanced Algorithms; it is optional for students on the MSc Applicable Mathematics who take MA421 Advanced Algorithms. 

Good general knowledge of mathematics, including familiarity with abstract concepts. A willingness to cope with technical details of computer usage, and with a rapid introduction to programming.

Introduction to programming in Java.  Introduction to the theory of algorithms: running time and correctness of an algorithm.  Recursion.  Data structures:  arrays, linked lists, stacks, queues, binary search trees.  Sorting algorithms.  Greedy algorithms.  Dynamic programming. Inheritance and Generics in Java.

This course is delivered through a combination of seminars and lectures totalling a minimum of 30 hours across Michaelmas Term. There are also optional computer help sessions for this course. Before the start of Michaelmas Term, there will be 6 hours of pre-sessional programming tutorials.

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

R Sedgewick, K Wayne, Introduction to programming in Java.

T H Cormen, C E Leiserson, R L Rivest and C Stein, Introduction to Algorithms.

Exam (65%, duration: 2 hours and 30 minutes) in the summer exam period.
Coursework (25%) in the MT.
Continuous assessment (10%).