Foundations of Machine Learning and AI

This specialisation combines mathematical theory with computational methods and explores the foundations of modern machine learning and artificial intelligence. You will develop a deeper understanding of how mathematical and statistical techniques can be used to build, analyse, and improve intelligent systems.

Courses include learning about neural networks, from their theoretical foundations to applying them to problems in areas such as computer vision. You can also explore topics such as algorithms, for analysing problems and designing efficient solutions, and spatial statistics.

Examples of what you can work with:

• Development and analysis of machine learning algorithms.

• Computer vision and image analysis.

• AI systems for prediction, optimisation, and decision support.

• Large-scale data analysis and statistical learning.

Graduates acquire strong skills in machine learning, optimisation, statistical modelling, and algorithm development, opening opportunities in AI, data science, software engineering, and research-intensive industries.

Requirements

The requirements for the Master's programme Mathematics, Statistics and Data Science apply to this specialisation.

How to select a specialisation

You may choose this specialisation after you have been admitted and enrolled. Only one specialisation can be selected.