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: No
Guidelines for interpreting course guide information

Course selection videos

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Personal development skills

  • Self-management
  • Problem solving
  • Application of information skills
  • Communication
  • Application of numeracy skills
  • Specialist skills