Dr Tugkan Batu

This course is available on the BSc in Business Mathematics and Statistics, BSc in Management, BSc in Mathematics and Economics, BSc in Mathematics with Economics and BSc in Mathematics, Statistics and Business. This course is available as an outside option to students on other programmes where regulations permit. This course is available with permission to General Course students.

Introduction to Abstract Mathematics (MA103), or an equivalent course giving a background in rigorous mathematics. Basic knowledge of Python programming is highly desirable.

Introduction to theory of algorithms guided by basic Python programming. Algorithmic thinking: Do you know how to multiply integers? Basic toolkit for the design and analysis of algorithms, and an in-depth study of sorting algorithms: Running time, Recurrence relations, Big-O notation, Correctness, Finite induction, Loop invariants. Optimal comparison sorts, and sorting in linear time. Tour of the most important data structures, fundamental algorithms, and algorithm design techniques: Lists, Stacks, Queues, Hashing. Breadth-first search, Depth-first search, Prim's algorithm, Dijkstra's algorithm, Maximum Flow. Incremental and recursive algorithms, Divide-and-Conquer, Greedy algorithms, Master Theorem. A selection of special topics.

This course is delivered through a combination of classes and lectures totalling a minimum of 30 hours across Michaelmas Term. This year, some or all of this teaching will be delivered through a combination of online classes and lectures delivered as online prerecorded videos.

Written answers to set problems will be expected on a weekly basis.

T H Cormen, C E Leiserson & R L Rivest, Introduction to Algorithms, MIT Press 1990 (or 2nd edn, 2001 or 3rd edn, 2009)

Exam (80%, duration: 2 hours) in the summer exam period.
Coursework (20%) in the MT.

Department: Mathematics

Total students 2019/20: 90

Average class size 2019/20: 18

Capped 2019/20: No

Value: Half Unit