MA407 Half Unit
Algorithms and Computation
This information is for the 2025/26 session.
Course Convenor
Dr Tugkan Batu
Availability
This course is compulsory on the MSc in Mathematics and Computation. This course is available on the MPA in Data Science for Public Policy, MSc in Data Science, 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 with permission as an outside option to students on other programmes where regulations permit.
The course is compulsory for students on the MSc Mathematics and Computation.
Requisites
Additional requisites:
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.
Course content
Introduction to programming in Python. 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. Online algorithms.
Teaching
10 hours of seminars and 22 hours of lectures in the Autumn Term.
There are also optional computer help sessions for this course. Before the start of Autumn Term, there will be 6 hours of pre-sessional programming tutorials.
Formative assessment
Problem sets
Weekly exercises are set and marked. Many of these will require implementation of programming exercises in Python.
Indicative reading
T H Cormen, C E Leiserson, R L Rivest and C Stein, Introduction to Algorithms.
Assessment
Exam (75%), duration: 120 Minutes in the January exam period
Problem sets (15%)
Continuous assessment (10%)
Key facts
Department: Mathematics
Course Study Period: Autumn Term
Unit value: Half unit
FHEQ Level: Level 7
CEFR Level: Null
Total students 2024/25: 36
Average class size 2024/25: 18
Controlled access 2024/25: NoCourse selection videos
Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.
Personal development skills
- Self-management
- Problem solving
- Application of information skills
- Communication
- Application of numeracy skills
- Specialist skills