THE UNIVERSITY of EDINBURGH

DEGREE REGULATIONS & PROGRAMMES OF STUDY 2019/2020

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DRPS : DPTs : School of Informatics DPTs

Jump to: Year 1, Year 2

Year 1 Academic year: 2019/20, Starting in: September

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

During both 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

Informatics Research Review

Course options

These are courses in Machine Learning, Statistics, and Optimization open to taught postgraduate students.

Data Mining and Exploration

Reinforcement Learning

Machine Learning and Pattern Recognition

Machine Learning Practical

Probabilistic Modelling and Reasoning

Natural Computing

Introductory Applied Machine Learning

Statistical Learning

Statistical Methodology

Applied Statistics

The Analysis of Survival Data

Fundamentals of Optimization

Time Series

Modern Optimization Methods for Big Data Problems

Large Scale Optimization for Data Science

Bayesian Data Analysis

Statistical Programming

Bayesian Theory

Incomplete Data Analysis

Nonparametric Regression Models

Generalised Regression Models

Integer and Combinatorial Optimization

Topics in Applied Optimization

AND

These are courses in Databases and Data Management Systems open to taught postgraduate students.

Algorithms and Data Structures

Database Systems

Advanced Databases (Level 11)

Applied Databases

Extreme Computing

Advanced Topics in Foundations of Databases

Algorithmic Foundations of Data Science

Usable Security and Privacy

Fundamentals of Data Management

AND

These are courses in Unstructured Data and Applications open to taught postgraduate students.

Bioinformatics 2

Advanced Vision (Level 11)

Automatic Speech Recognition

Neural Information Processing

Social and Technological Networks

Accelerated Natural Language Processing

Image and Vision Computing

Text Technologies for Data Science

Natural Language Understanding, Generation, and Machine Translation

Bioinformatics 1

Data Visualisation

Speech Synthesis

Optimization Methods in Finance

Biomedical Data Science

AND

These are courses in all schools other than Medicine or Veterinary Studies. Note this includes courses within the School of Informatics.

Year 2 Academic year: 2019/20, Starting in: September

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

During both 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'.

The dissertation requires a period of full-time study after the Semester 2 exams for the courses.

Compulsory courses

MSc Dissertation (Informatics)

Must be passed at 50%

Informatics Project Proposal

Course options

These are courses in Machine Learning, Statistics, and Optimization open to taught postgraduate students.

Data Mining and Exploration

Reinforcement Learning

Machine Learning and Pattern Recognition

Machine Learning Practical

Probabilistic Modelling and Reasoning

Natural Computing

Introductory Applied Machine Learning

Statistical Learning

Statistical Methodology

Applied Statistics

The Analysis of Survival Data

Fundamentals of Optimization

Time Series

Modern Optimization Methods for Big Data Problems

Large Scale Optimization for Data Science

Bayesian Data Analysis

Statistical Programming

Bayesian Theory

Incomplete Data Analysis

Nonparametric Regression Models

Generalised Regression Models

Integer and Combinatorial Optimization

Topics in Applied Optimization

AND

These are courses in all schools other than Medicine or Veterinary Studies.

AND

These are courses in Databases and Data Management Systems open to taught postgraduate students.

Algorithms and Data Structures

Database Systems

Advanced Databases (Level 11)

Applied Databases

Extreme Computing

Advanced Topics in Foundations of Databases

Algorithmic Foundations of Data Science

Usable Security and Privacy

Fundamentals of Data Management

AND

These are courses in Unstructured Data and Applications open to taught postgraduate students.

Bioinformatics 2

Advanced Vision (Level 11)

Automatic Speech Recognition

Neural Information Processing

Social and Technological Networks

Accelerated Natural Language Processing

Image and Vision Computing

Text Technologies for Data Science

Natural Language Understanding, Generation, and Machine Translation

Bioinformatics 1

Data Visualisation

Speech Synthesis

Optimization Methods in Finance

Biomedical Data Science

AND

These are courses in all schools other than Medicine and Veterinary Medicine. Note this includes courses within the School of Informatics.

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