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MSc in Mathematics and Computation

Programme Code: TMMACOM

Department: Mathematics

For students starting this programme of study in 2025/26

Guidelines for interpreting programme regulations

Classification scheme for the award of a taught master's degree (four units)
Exam sub-board local rules

Full year programme. Students must take courses to the value of four full units.

Please note that places are limited on some optional courses. Admission onto any particular course is not guaranteed and may be subject to timetabling constraints and/or students meeting specific prerequisite requirements.

Paper

Course number, title (unit value)

Paper 1

A

MA407 Algorithms and Computation (0.5) #

Papers 2, 3 & 4

Courses to the value of 1.5 unit(s) from the following: B C D

MA402 Mathematical Game Theory (0.5) #

MA408 Topics in Discrete Mathematics (0.5) # (suspended 2025/26)

MA409 Continuous Time Optimisation (0.5) #

MA411 Probability and Measure (0.5) #

MA421 Topics in Algorithms (0.5) #

MA427 Nonlinear Optimisation and Applications (0.5) #

MA428 Combinatorial Optimisation (0.5) #

MA429 Algorithmic Techniques in Machine Learning (0.5) #

MA433 Mathematics of Networks (0.5) #

MA434 Algorithmic Game Theory (0.5) # (suspended 2025/26)

MA435 Machine Learning in Financial Mathematics (0.5) #

MA436 Mathematics of Cryptocurrencies and the Blockchain (0.5) #

MA437 Learning Dynamics in Games (0.5)

Papers 5 & 6

Courses to the value of 1.0 unit(s) from the following:

EC484 Econometric Analysis (1.0) #

EC487 Advanced Microeconomics (1.0) #

FM402 Financial Risk Analysis (0.5) #

FM429 Asset Markets A (0.5) #

FM441 Derivatives (0.5) #

FM442 Quantitative Methods for Finance and Risk Analysis (0.5) #

ST409 Stochastic Processes (0.5) #

ST418 Advanced Time Series Analysis (0.5) #

ST455 Reinforcement Learning (0.5) #

ST456 Deep Learning (0.5) #

ST459 Quantum Computation and Information (0.5) #

ST463 Stochastic Simulation, Training, and Calibration (0.5) #

Papers 2, 3 & 4 options list

Or any other paper with the approval of the Programme Director and the teacher responsible for the course, excluding MA415, MA416, MA417 and MA424.

Paper 7

MA498 Dissertation in Mathematics (1.0)

(OR)

MA497 Project in Mathematics (0.5)

Plus one 0.5 unit option from Papers 2, 3 & 4:

Papers 2, 3 & 4 options list

Papers 2, 3 & 4 options list

MA402 Mathematical Game Theory (0.5) #

MA408 Topics in Discrete Mathematics (0.5) # (suspended 2025/26)

MA409 Continuous Time Optimisation (0.5) #

MA411 Probability and Measure (0.5) #

MA421 Topics in Algorithms (0.5) #

MA427 Nonlinear Optimisation and Applications (0.5) #

MA428 Combinatorial Optimisation (0.5) #

MA429 Algorithmic Techniques in Machine Learning (0.5) #

MA433 Mathematics of Networks (0.5) #

MA434 Algorithmic Game Theory (0.5) # (suspended 2025/26)

MA435 Machine Learning in Financial Mathematics (0.5) #

MA436 Mathematics of Cryptocurrencies and the Blockchain (0.5) #

MA437 Learning Dynamics in Games (0.5)

Footnotes

# means there may be prerequisites for this course. Please view the course guide for more information.

A: Paper 1, MA407: Upon supplying satisfactory evidence to the course convenor of relevant previous courses taken, a student may be exempted from MA407 at the discretion of the Programme Director. A student shall replace MA407 with MA421, subject to approval of the Programme Director.

B: Papers 2, 3 & 4, MA402: This option will not be available to those who have already studied MA300 and MA301, or who have studied this subject as part of an undergraduate degree.

C: Papers 2, 3 & 4, MA433: This option will not be available to those who have already studied MA320.

D: Papers 2, 3 & 4, MA436: This option will not be available to those who have already studied MA336.

Note for prospective students:
For changes to graduate course and programme information for the next academic session, please see the graduate summary page for prospective students. Changes to course and programme information for future academic sessions can be found on the graduate summary page for future students.