High Drop-out Rate Alert
17% of students drop out or transfer from this specific course. Consider asking why on an open day.
BSc Mathematics with Machine Learning
About this course
Mathematics with Machine Learning is a degree that reflects one of the most significant developments in contemporary science and technology. Machine learning, the field concerned with building systems that learn patterns from data and improve their performance through experience, rests on deep mathematical foundations. Without linear algebra, calculus, probability theory, and optimisation, the algorithms that power image recognition, language models, recommendation systems, and scientific modelling cannot be understood at any meaningful level. This programme gives you both the mathematical rigour and the computational skills to work at the frontier of a rapidly evolving field. At the University of Portsmouth, this three-year full-time programme combines a thorough grounding in core mathematics with focused study of the theory and methods behind machine learning. You will develop expertise in pure and applied mathematics, mathematical modelling, statistical inference, and computational methods, and you will apply these to the design, analysis, and evaluation of learning algorithms. The programme includes a sandwich year, giving you the opportunity to spend time in a professional environment, whether in a technology company, a research institution, or a data-driven organisation, before completing your studies. A year abroad is also available, and there is a work placement component that further strengthens the connection between academic study and professional practice. The combination of rigorous mathematical training and machine learning specialisation develops a profile that is genuinely distinctive. You will be able to engage with algorithms at a level of depth that goes beyond tool use, reasoning about why methods work, where they fail, and how they can be improved. You will also develop strong programming skills and the ability to communicate technical ideas clearly to different audiences. Graduates pursue careers in data science, software engineering, artificial intelligence research, quantitative finance, bioinformatics, and academic research. Many go on to postgraduate study, including taught masters or doctoral programmes in machine learning, statistics, or applied mathematics. The demand for people who can combine mathematical understanding with computational expertise continues to grow across almost every sector.
Syllabus & Modules
Typical curriculumStudent Satisfaction
National Student Survey - 35 respondents (94% response rate)
Similarly Ranked Alternatives
What comes next? π
Choosing the right university starts with choosing the right school. Explore transparent, data-driven school profiles powered by official DfE statistics.
Explore Schools on WhatSchool.ai β