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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2018/2019
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Degree Programme Table: Data Science (MSc)(R) (PRMSCDATSC1F)

Jump to: Year 1

Year 1 Academic year: 2018/19, Starting in: September

Notes:
Before selecting your outside courses, please ensure you have met your Personal Tutor.

Compulsory courses

You must take these courses
Introduction to Research in Data Science
INFR11138 20 credits

Course options

Group A

Select exactly 160 credits in this group.

MSc by Research Thesis (Data Science)

Select exactly 90 credits of the following courses
MSc by Research Thesis (Data Science)
INFR11106 90 credits
AND

Courses from School(s) O-P - DSCDT - MACHINE LEARNING - Level(s) 9-11

Select between 10 and 40 credits of the following courses
Notes:
These are courses in Machine Learning, Statistics, and Optimization open to taught postgraduate students.
Data Mining and Exploration
INFR11007 10 credits
Reinforcement Learning
INFR11010 10 credits
Machine Learning and Pattern Recognition
INFR11130 20 credits
Machine Learning Practical
INFR11132 20 credits
Probabilistic Modelling and Reasoning
INFR11134 20 credits
Introductory Applied Machine Learning
INFR11182 20 credits
Statistical Learning
MATH10094 10 credits
Statistical Methodology
MATH10095 10 credits
Applied Statistics
MATH10096 10 credits
The Analysis of Survival Data
MATH11024 10 credits
Fundamentals of Optimization
MATH11111 10 credits
Time Series
MATH11131 10 credits
Modern Optimization Methods for Big Data Problems
MATH11146 10 credits
Large Scale Optimization for Data Science
MATH11147 10 credits
Biomedical Data Science
MATH11174 10 credits
Bayesian Data Analysis
MATH11175 10 credits
Statistical Programming
MATH11176 10 credits
Bayesian Theory
MATH11177 10 credits
Incomplete Data Analysis
MATH11185 10 credits
Nonparametric Regression Models
MATH11186 10 credits
Generalised Regression Models
MATH11187 10 credits
Integer and Combinatorial Optimization
MATH11192 10 credits
Topics in Applied Optimization
MATH11194 10 credits
AND

Courses from School(s) O - DSCDT - DATABASES - Level(s) 10-11

Select between 10 and 40 credits of the following courses
Notes:
These are courses in Databases and Data Management Systems open to taught postgraduate students.
Algorithms and Data Structures
INFR10052 10 credits
Database Systems
INFR10070 20 credits
Applied Databases
INFR11015 10 credits
Extreme Computing
INFR11088 10 credits
Advanced Topics in Foundations of Databases
INFR11122 20 credits
Algorithmic Foundations of Data Science
INFR11156 10 credits
Usable Security and Privacy
INFR11158 10 credits
Fundamentals of Data Management
PGPH11088 10 credits
AND

Courses from School(s) O/I/P - DSCDT - APPS - Level(s) 11

Select between 10 and 40 credits of the following courses
Notes:
These are courses in Unstructured Data and Applications open to taught postgraduate students.
Foundations of Natural Language Processing
INFR09028 10 credits
Bioinformatics 2
INFR11005 10 credits
Advanced Vision (Level 11)
INFR11031 10 credits
Automatic Speech Recognition
INFR11033 10 credits
Neural Information Processing
INFR11035 10 credits
Social and Technological Networks
INFR11124 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
Bioinformatics 1
INFR11160 10 credits
Speech Synthesis
LASC11062 10 credits
Optimization Methods in Finance
MATH11158 10 credits
AND

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

Select between 0 and 30 credits from Level 11 courses in Schedules A to Q, T and W
Notes:
This refers to all level 11 courses in all schools other than Medicine or Veterinary Studies.
AND

Level 9 and 10 courses in Schedules A to Q, T and W

Select between 0 and 10 credits from Level 9 and 10 courses in Schedules A to Q, T and W
Notes:
This refers to all level 9 and 10 courses in all schools other than Medicine or Veterinary Studies.
OR

Group B

Select exactly 160 credits in this group.

MSc by Research Thesis (Data Science; 120pt)

Select exactly 120 credits of the following courses
MSc by Research Thesis (Data Science; 120pt)
INFR11107 120 credits
AND

Courses from School(s) O-P - Data Science (MSc)(R)120 - Level(s) 9-11

Select exactly 40 credits of the following courses
Foundations of Natural Language Processing
INFR09028 10 credits
Introductory Applied Machine Learning
INFR10069 20 credits
Bioinformatics 2
INFR11005 10 credits
Reinforcement Learning
INFR11010 10 credits
Applied Databases
INFR11015 10 credits
Bioinformatics 1
INFR11016 10 credits
Advanced Vision (Level 11)
INFR11031 10 credits
Automatic Speech Recognition
INFR11033 10 credits
Neural Information Processing
INFR11035 10 credits
Natural Language Understanding (Level 11)
INFR11061 10 credits
Machine Translation (Level 11)
INFR11062 10 credits
Extreme Computing
INFR11088 10 credits
Advanced Topics in Foundations of Databases
INFR11122 20 credits
Accelerated Natural Language Processing
INFR11125 20 credits
Machine Learning and Pattern Recognition
INFR11130 20 credits
Machine Learning Practical
INFR11132 20 credits
Probabilistic Modelling and Reasoning
INFR11134 20 credits
Text Technologies for Data Science
INFR11145 20 credits
Speech Synthesis
LASC11062 10 credits
Stochastic Optimization
MATH11010 5 credits
The Analysis of Survival Data
MATH11024 10 credits
Combinatorial Optimization
MATH11030 5 credits
Nonlinear Optimization
MATH11031 10 credits
Statistical Theory
MATH11085 10 credits
Statistical Regression Models
MATH11086 10 credits
Fundamentals of Optimization
MATH11111 10 credits
Likelihood and Generalized Linear Models
MATH11121 10 credits
Modern Optimization Methods for Big Data Problems
MATH11146 10 credits
Large Scale Optimization for Data Science
MATH11147 10 credits
Optimization Methods in Finance
MATH11158 10 credits
Biomedical Data Science
MATH11174 10 credits
Bayesian Data Analysis
MATH11175 10 credits
Statistical Programming
MATH11176 10 credits
Bayesian Theory
MATH11177 10 credits
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