Taught course

Machine Learning in Science

University of Nottingham · School of Physics and Astronomy

Entry requirements

A 2.1 (or international equivalent) in one of the following areas: physics, mathematics, computer science, chemistry, engineering. A 2.2 (or international equivalent) may be considered if the applicant has relevant work experience or another supporting factor.

Months of entry


Course content

In the last few years the development and use of ML and AI have revolutionised areas such as computer vision, speech recognition and natural language processing, transforming them from almost intractable problems into useful aspects of our everyday lives.

AI is also fast becoming essential in science for analysing and classifying large sets of data coming from ever more numerous observations and complex experiments. At the same time, the growing interest in the use of ML methods has led to new approaches to AI by applying the ideas and techniques of physical sciences which offer distinct and complementary perspectives to those of computer science and software engineering.

The interplay between AI and scientific thinking is central to the spirit of this course. It will provide you with high quality training, covering the basic theory of ML with particular emphasis on the application to concrete science problems in the form of research projects.

The training in the application of ML and AI techniques to concrete problems of scientific relevance, helps build the skills that are sought after in research and in industry, enhancing your employability in a rapidly expanding area.

Qualification and course duration


full time
12 months

Course contact details

Postgraduate enquiries
+44 (0)115 951 5559