Accelerate your career in industry or research with this online, part-time master’s course, integrating mathematical rigor with practical machine learning and data science skills.

You’ll gain expertise in tackling complex data by implementing scalable solutions using industry-standard tools, including PySpark. You’ll enhance your analytical abilities in mathematics and statistics and also explore the limitations of machine learning methods and learn how to ethically apply these techniques to your work.

This course covers a diverse range of topics in theoretical and applied perspectives, focusing on statistical estimation, prediction and anomaly detection. Topics also include fundamentals of probability and decision theory, advanced deep learning, reinforcement learning techniques, supervised and unsupervised learning, Bayesian methods and unstructured data processing.

Finally, you will have the opportunity to apply the knowledge you have gained from the taught programme through an extensive research project, carried out in collaboration with a member of academic staff.

All learning is delivered online.