Component

MA Public Opinion and Political Behaviour
PhD Data Science options

Year 1, Component 02

Option from List A
MA214-7-SP
Network Analysis
(15 CREDITS)

Everything in the world is linked together. This module introduces you to the knowledge of “networks” to disclose the mystery behind these links. An introduction to networks, the most common types of networks, and their mathematical properties, as well as typical network models, will be delivered in this module. You will also learn programming skills using Python/R to create and analyse real-world networks.

MA304-7-SP
Data Visualisation
(15 CREDITS)

In a world increasingly driven by data, the need for analysis and visualisation is more important than ever. In this module you will look at data through the eyes of a numerical detective. You will work on the lost art of exploratory data analysis, reviewing appropriate methods for data summaries with the aim to summarise, understand, extract hidden patterns and identify relationships. You will then work on graphical data analysis, using simple graphs to understand the data, but also advanced complex methods to scrutinise data and interactive plots to communicate data information to a wider audience. For data analysis and visualisations you will use R-studio, and a combination of R-shiny applications and google visualisations for interactive plotting.

MA305-7-AU
Nonlinear Programming
(15 CREDITS)

How do you apply an algorithm or numerical method to a problem? What are the advantages? And the limitations? Understand the theory and application of nonlinear programming. Learn the principles of good modelling and know how to design algorithms and numerical methods. Critically assess issues regarding computational algorithms.

MA306-7-AU
Combinatorial Optimisation
(15 CREDITS)

In this module you will learn what underpins the algorithms used where variables are integer and apply these algorithms to solve integer and mixed integer problems with cutting-plane algorithms.

MA318-7-AU
Statistical Methods
(15 CREDITS)

This module will enable you to expand your knowledge on multiple statistical methods. You will learn the concepts of decision theory and how to apply them, have the chance to explore “Monte Carlo” simulation, and develop an understanding of Bayesian inference, and the basic concepts of a generalised linear model.

MA319-7-AU
Stochastic Processes
(15 CREDITS)

Ever considered becoming an Actuary? This module covers the required material for the Institute and Faculty of Actuaries CT4 and CT6 syllabus. It explores the stochastic process and principles of actuarial modelling alongside time series models and analysis.

MA332-7-AU
Databases and data processing with SQL
(15 CREDITS)

Relational databases and SQL are developed and used as a fundamental tool for relevant applications from different disciplines including humanities, life sciences, linguistics, marketing and social science. They are essential to the efficient information management for IT systems and commercial applications in almost all modern organisations. The purpose of this module is to provide you with an introduction to the underlying principles and practical experience of the design and implementation of relational databases. It will cover the data modelling and SQL, database analysis, design and management, and advanced topics including big data, security and privacy issues of modern databases.

MA338-7-SP
Dynamic programming and reinforcement learning
(15 CREDITS)

Are you interested in understanding how AlphaGo was able to beat a top Go player? In this module, you will learn about the models behind successful stories of Reinforcement Learning, where a machine (agent) makes sequential decisions to reach an optimal goal. The lectures will be complemented with Lab sessions where we will take advantage of the Open AI Gym environments, allowing us to train our agents to perform tasks such as playing videogames (Atari) and more.

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