THE UNIVERSITY of EDINBURGH

DEGREE REGULATIONS & PROGRAMMES OF STUDY 2024/2025

Timetable information in the Course Catalogue may be subject to change.
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Degree Programme Table: Data Science (MSc) (Part-time) - 3 Years (PTMSCDATSC2P)

Jump to: Year 1, Year 2, Year 3

Year 1 Academic year: 2024/25, Starting in: September

Notes:
Before making your course choices, make sure you have discussed them with your Personal Tutor.

During the first two years of this programme, students are permitted to take a maximum of 30 credits of courses that are below level 11 or not individually listed below.

Over the first two years, at least 10 credits must be selected from each of the three topic groupings:
'Machine Learning, Statistics and Optimization',
'Databases and Data Management', and
'Data Science Applications'.

Compulsory courses

You must take these courses
Informatics Research Review
INFR11136 10 credits

Course options

Group A

Select exactly 50 credits in this group.

Informatics MSc DS Level 10-11 Machine Learning and Statistics Courses

Select between 0 and 50 credits of the following courses
Notes:
These are courses in Machine Learning, Statistics, and Optimization open to taught postgraduate students.
Reinforcement Learning
INFR11010 10 credits
Machine Learning and Pattern Recognition
INFR11130 20 credits
Machine Learning Practical
INFR11132 20 credits
Machine Learning Theory
INFR11202 10 credits
Applied Machine Learning
INFR11211 20 credits
Simulation, Analysis, and Validation of Computational Models
INFR11254 10 credits
Statistical Methodology
MATH10095 10 credits
Applied Statistics
MATH10096 10 credits
Fundamentals of Optimization
MATH11111 10 credits
Time Series
MATH11131 10 credits
Large Scale Optimization for Data Science
MATH11147 10 credits
Bayesian Data Analysis
MATH11175 10 credits
Statistical Programming
MATH11176 10 credits
Bayesian Theory
MATH11177 10 credits
Incomplete Data Analysis
MATH11185 10 credits
Generalised Regression Models
MATH11187 10 credits
Integer and Combinatorial Optimization
MATH11192 10 credits
Targeted Causal Learning
MATH11238 10 credits
AND

Informatics MSc DS Level 10-11 Data Management Courses

Select between 0 and 50 credits of the following courses
Notes:
These are courses in Databases and Data Management Systems open to taught postgraduate students.
Fundamentals of Data Management
EPCC11005 10 credits
Algorithms and Data Structures
INFR10052 10 credits
Introduction to Databases
INFR10080 20 credits
Distributed Systems (Level 11)
INFR11022 10 credits
Advanced Database Systems
INFR11199 20 credits
Programming for Data Science at Scale
INFR11255 10 credits
Machine Learning Systems
INFR11269 20 credits
AND

Informatics MSc DS Level 11 Applications Courses

Select between 0 and 50 credits of the following courses
Notes:
These are courses in Unstructured Data and Applications open to taught postgraduate students.
Distributed Systems (Level 11)
INFR11022 10 credits
Automatic Speech Recognition
INFR11033 10 credits
Accelerated Natural Language Processing
INFR11125 20 credits
Text Technologies for Data Science
INFR11145 20 credits
Natural Language Understanding, Generation, and Machine Translation
INFR11157 20 credits
Data-driven Business and Behaviour Analytics
INFR11198 20 credits
Case Studies in AI Ethics (CSAI)
INFR11206 10 credits
Methods for Causal Inference
INFR11207 10 credits
Computer Vision
INFR11212 20 credits
Programming for Biomedical Informatics
INFR11260 10 credits
Speech Synthesis
LASC11062 10 credits
Optimization Methods in Finance
MATH11158 10 credits
AND

Level 10 and 11 courses in Schedules A to Q, T and W

Select between 0 and 20 credits from Level 10 and 11 courses in Schedules A to Q, T and W
Notes:
These are courses in all schools other than Medicine, Veterinary Studies, or the Centre for Open Learning. Note this includes courses within the School of Informatics.

Students may not register for introductory programming courses in other parts of the University unless explicitly listed in the DPT

Year 2 Academic year: 2024/25, Starting in: September

Notes:
Before making your course choices, make sure you have discussed them with your Personal Tutor.

During the first two years of this programme, students are permitted to take a maximum of 30 credits of courses that are below level 11 or not individually listed below.

Over the first two years, at least 10 credits must be selected from each of the three topic groupings:
'Machine Learning, Statistics and Optimization',
'Databases and Data Management', and
'Data Science Applications'.

Compulsory courses

You must take these courses
Informatics Project Proposal
INFR11147 10 credits

Course options

Group A

Select exactly 50 credits in this group.

Informatics MSc DS Level 10-11 Machine Learning and Statistics Courses

Select between 0 and 50 credits of the following courses
Notes:
These are courses in Machine Learning, Statistics, and Optimization open to taught postgraduate students.
Reinforcement Learning
INFR11010 10 credits
Machine Learning and Pattern Recognition
INFR11130 20 credits
Machine Learning Practical
INFR11132 20 credits
Machine Learning Theory
INFR11202 10 credits
Applied Machine Learning
INFR11211 20 credits
Simulation, Analysis, and Validation of Computational Models
INFR11254 10 credits
Statistical Methodology
MATH10095 10 credits
Applied Statistics
MATH10096 10 credits
Fundamentals of Optimization
MATH11111 10 credits
Time Series
MATH11131 10 credits
Large Scale Optimization for Data Science
MATH11147 10 credits
Bayesian Data Analysis
MATH11175 10 credits
Statistical Programming
MATH11176 10 credits
Bayesian Theory
MATH11177 10 credits
Incomplete Data Analysis
MATH11185 10 credits
Generalised Regression Models
MATH11187 10 credits
Integer and Combinatorial Optimization
MATH11192 10 credits
Targeted Causal Learning
MATH11238 10 credits
AND

Informatics MSc DS Level 10-11 Data Management Courses

Select between 0 and 50 credits of the following courses
Notes:
These are courses in Databases and Data Management Systems open to taught postgraduate students.
Fundamentals of Data Management
EPCC11005 10 credits
Algorithms and Data Structures
INFR10052 10 credits
Introduction to Databases
INFR10080 20 credits
Distributed Systems (Level 11)
INFR11022 10 credits
Advanced Database Systems
INFR11199 20 credits
Programming for Data Science at Scale
INFR11255 10 credits
Machine Learning Systems
INFR11269 20 credits
AND

Informatics MSc DS Level 11 Applications Courses

Select between 0 and 50 credits of the following courses
Notes:
These are courses in Unstructured Data and Applications open to taught postgraduate students.
Distributed Systems (Level 11)
INFR11022 10 credits
Automatic Speech Recognition
INFR11033 10 credits
Accelerated Natural Language Processing
INFR11125 20 credits
Text Technologies for Data Science
INFR11145 20 credits
Natural Language Understanding, Generation, and Machine Translation
INFR11157 20 credits
Data-driven Business and Behaviour Analytics
INFR11198 20 credits
Case Studies in AI Ethics (CSAI)
INFR11206 10 credits
Methods for Causal Inference
INFR11207 10 credits
Computer Vision
INFR11212 20 credits
Programming for Biomedical Informatics
INFR11260 10 credits
Speech Synthesis
LASC11062 10 credits
Optimization Methods in Finance
MATH11158 10 credits
AND

Level 10 and 11 courses in Schedules A to Q, T and W

Select between 0 and 20 credits from Level 10 and 11 courses in Schedules A to Q, T and W
Notes:
These are courses in all schools other than Medicine, Veterinary Studies, or the Centre for Open Learning. Note this includes courses within the School of Informatics.

Students may not register for introductory programming courses in other parts of the University unless explicitly listed in the DPT

Year 3 Academic year: 2024/25, Starting in: September

Notes:
Before making your course choices, make sure you have discussed them with your Personal Tutor.

Compulsory courses

You must take these courses
MSc Dissertation (Informatics)

Must be passed at 50%

INFR11077 60 credits
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