THE UNIVERSITY of EDINBURGH

DEGREE REGULATIONS & PROGRAMMES OF STUDY 2026/2027

Timetable information in the Course Catalogue may be subject to change.
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Degree Programme Table: Computational Applied Mathematics (MSc) - 1 Year (Full-time) (PTMSCCOMAM1F)

Jump to: Year 1

Year 1 Academic year: 2026/27, Starting in: September

Notes:
Students must take at least 90 credits of taught courses at Level 11. Equivalently, they may take no more than 30 credits of Level 10 courses, including the compulsory 10 credits of Numerical Linear Algebra (MATH10098).

Students must take an even credit load of taught courses in semester 1 and semester 2.

Compulsory courses

You must take these courses
Industrial Mathematics

Must be taken during Semester 1

MATH11231 10 credits
Numerical Linear Algebra

Must be taken during Semester 1

MATH10098 10 credits
Applied Dynamical Systems

Must be taken during Semester 2

MATH11140 10 credits
Numerical Partial Differential Equations

Must be taken during Semester 2

MATH11207 10 credits
Research Skills for Computational Applied Mathematics

Must be taken during Full Year

MATH11197 20 credits
Dissertation (CAM)

Must be taken during Block 5 (Sem 2) and beyond

MATH11195 60 credits

Course options

Group A

Select between 0 and 20 credits in this group.

CAM: Machine learning stream recommended courses

Select between 0 and 20 credits of the following courses
Machine Learning in Python
MATH11205 10 credits
Numerical Methods for Data
MATH11240 10 credits
OR

Group B

Select between 0 and 30 credits in this group.

CAM: Fluids and plasmas stream recommended courses

Select between 0 and 30 credits of the following courses
Fluid Dynamics
MATH11248 10 credits
Magnetohydrodynamics I
MATH11267 10 credits
Magnetohydrodynamics II
MATH11268 10 credits
OR

Group C

Select between 0 and 20 credits in this group.

CAM: Computational science stream recommended courses

Select between 0 and 20 credits of the following courses
Numerical Ordinary Differential Equations and Applications
MATH10060 10 credits
Numerical Methods for Data
MATH11240 10 credits
AND

Group D

Select between 0 and 30 credits in this group.

CAM Introductory Courses

Select between 0 and 10 credits of the following courses
Notes:
Statistical Methodology (MATH10095) is only for students who need extra background in the topic. It is not suitable for students who have taken an equivalent introductory course in a previous degree. You must gain approval from your cohort lead before registering for this course.
Selected courses must be taken during Semester 1
Statistical Methodology
MATH10095 10 credits
AND

CAM: Semester 1 Options

Select between 0 and 30 credits of the following courses
Mathematical Biology
MATH10013 10 credits
Applied Stochastic Differential Equations
MATH10053 10 credits
Stochastic Modelling (Postgraduate Taught)
MATH11029 10 credits
Fundamentals of Optimization
MATH11111 10 credits
Statistical Programming
MATH11176 10 credits
Bayesian Theory
MATH11177 10 credits
Python Programming
MATH11199 10 credits
Machine Learning in Python
MATH11205 10 credits
Fluid Dynamics
MATH11248 10 credits
Magnetohydrodynamics I
MATH11267 10 credits
AND

Group E

Select between 0 and 30 credits in this group.

CAM: Semester 2 Options

Select between 0 and 30 credits of the following courses
High Performance Data Analytics
EPCC11014 10 credits
Numerical Ordinary Differential Equations and Applications
MATH10060 10 credits
Time Series
MATH11131 10 credits
Large Scale Optimization for Data Science
MATH11147 10 credits
Optimization Methods in Finance
MATH11158 10 credits
Bayesian Data Analysis
MATH11175 10 credits
Numerical Methods for Data
MATH11240 10 credits
Nonlinear Optimization
MATH11244 10 credits
Magnetohydrodynamics II
MATH11268 10 credits
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