This course is part of our master's programme in computer science.
The MSc in Data Science and Machine Learning draws on our internationally recognised research in data science and machine learning. It is informed by the expertise of our academic staff and reflects current research and practice in the field. The course develops your understanding of how to obtain data from a range of sources, alongside key methods for data pre-processing, cleaning, analytics, and modelling.
The programme offers three award routes that you can choose to study:
MSc Data Science and Machine Learning
MSc Data Science and Machine Learning with Extended Professional Practice
MSc Data Science and Machine Learning with Advanced Research
Why choose this course
Includes a one-year industry placement, enabling you to gain valuable commercial experience and enhance your employability.
One of a range of advanced courses within our postgraduate master's programme in computer science, this particular course provides you with a specialism in data science and machine learning.
You will be taught by a highly regarded and long-established computer science department, with 90% of its research ranked as world-leading (Research Excellence Framework, 2021).
Gain hands-on experience across the full lifecycle of data science and machine learning applications. You will study image processing, time series analysis, and natural language processing, with applications in finance, healthcare, marketing, and both real-time and historical data contexts.
Develop practical teamwork experience by applying skills in cloud computing, big data, machine learning, and data visualisation using industry-standard tools.
Build expertise using industry-relevant tools and practices, including system administration, cloud computing, software development, database administration, machine learning, and data visualisation. You will also learn to critically review and evaluate emerging technologies and research, enabling you to adapt to new challenges in data engineering.
Acquire fundamental mathematical knowledge essential for data science, including linear algebra, set theory, advanced calculus, probability, and statistics. You will learn to apply these foundations as computational techniques to solve real-world problems.
Explore research-informed topics in neural network theory and design, gaining insight into the technologies underpinning modern tools such as large language models. Teaching draws on the School’s research strengths in biocomputation, evolutionary algorithms, and neural networks.
