MA407      Half Unit
Algorithms and Computation

This information is for the 2024/25 session.

Teacher responsible

Dr Tugkan Batu

Availability

This course is available on the MPA in Data Science for Public Policy, 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) (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.

Pre-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

This course is delivered through a combination of seminars and lectures totalling a minimum of 30 hours across 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 coursework

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 (65%, duration: 2 hours) in the January exam period.
Coursework (25%) and continuous assessment (10%) in the AT.

Key facts

Department: Mathematics

Total students 2023/24: 51

Average class size 2023/24: 25

Controlled access 2023/24: No

Value: Half Unit

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