MA421      Half Unit
Advanced Algorithms

This information is for the 2021/22 session.

Teacher responsible

Prof Konrad Swanepoel


This course is available on the MSc in Applicable Mathematics and MSc in Operations Research & Analytics. This course is available as an outside option to students on other programmes where regulations permit.


Students must have completed Algorithms and Computation (MA407) or have taken an equivalent course to provide a basic knowledge in analysis of algorithms: running time and correctness of an algorithm, and basic knowledge of computer programming (preferably in Java). Students should be comfortable with proofs and proof techniques used in pure mathematics.

Course content

Introduction to NP-Completeness, followed by Approximation Algorithms, Randomised Algorithms, and other topics such as some of Average-Case Analysis, Streaming Algorithms, Exponential-Time Algorithms, and Numerical Algorithms.


This course is delivered through a combination of seminars and lectures totalling a minimum of 30 hours across Lent Term. This year, apart from pre-recorded lecture videos, there will be a weekly live online session of an hour. Depending on circumstances, seminars might be online.

Formative coursework

Weekly exercises are set and marked. Some of these will include programming exercises in Java.

Indicative reading

T. H. Cormen, C. E. Leiserson, R. L. Rivest and C. Stein, Introduction to Algorithms, 3rd ed., MIT;

M.R. Garey and D.S. Johnson, Computers and Intractability: A Guide to the Theory of NP-completeness, W.H. Freeman, 1979;

D. Williamson, D. B. Shmoys, The Design of Approximation Algorithms, Cambridge University Press 2011;

V. Vazirani, Approximation Algorithms, 2nd ed., Springer, 2002;

R. Motwani and P. Raghavan, Randomized Algorithms, Cambridge University Press 1995.


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

Course selection videos

Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.

Important information in response to COVID-19

Please note that during 2021/22 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the differing needs of students in attendance on campus and those who might be studying online. For example, this may involve changes to the mode of teaching delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.

Key facts

Department: Mathematics

Total students 2020/21: 8

Average class size 2020/21: 8

Controlled access 2020/21: No

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

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