Machine Learning University of Southampton

Overview

What you'll learn

You'll start by studying core concepts that underpin machine learning, including probability, linear algebra and statistical learning theory. You'll then explore advanced topics such as deep neural networks, Bayesian methods, active learning and reinforcement learning. 

You'll also learn how to design scalable, efficient models that work with large and complex data sets. Core teaching is supported by specialist optional modules so you can tailor the course to your interests.

On this machine learning course you'll:

• build a rigorous understanding of core machine learning and deep learning techniques
• analyse data sets and evaluate models using appropriate metrics
• use modern software tools to implement, train and test your own models
• engage with current research questions in machine learning

Through optional modules you'll be able to focus on areas that match your interests and goals. These may include topics such as data mining, natural language processing, computer vision or optimisation for machine learning, depending on current research and teaching expertise in the department.

Your research project

Your individual research project is a major part of the MSc. You'll work with an academic supervisor on an in-depth investigation, such as developing or evaluating a new method, or studying how a particular machine learning model makes decisions.

Through this project you'll build practical experience of planning and delivering a research study, from the initial question through to the final report. You'll build a portfolio of work you can use to support applications for PhD study or specialist roles in industry, and prepares you to contribute to future developments in the field.