MSc Advanced Data Science at University of Strathclyde

Programme overview

An advanced course for students with a degree that includes a significant mathematical component, building theoretical and practical skills in statistics and data science. It covers data analysis and machine learning, processing of big data, predictive modelling and the statistical software packages R and Python.

What you will study

Semester 1 covers big data processing, the mathematics behind prediction and classification, and programming in R and Python (e.g. Data Analytics in R, Big Data Fundamentals, Multivariate Analysis). Semester 2 covers machine learning, deep learning and interactive dashboards with RShiny, plus optional modules such as networks or game theory; Semester 3 is a research project.

Career pathways

Graduates work as statisticians, data analysts, software developers or engineers, statistical programmers and data scientists in investment companies, financial institutions, the pharmaceutical industry, medical research, government organisations, retailers and internet information providers.

Official programme page

Application information

Entry requirements

Minimum second-class (2:2) Honours degree or overseas equivalent in a mathematical discipline (for Australia and Canada, normal degrees are accepted). Applicants with relevant experience or appropriate professional qualifications are also welcome to apply. English language: IELTS 6.0 overall with no component below 5.5; TOEFL, PTE and other recognised tests also accepted. Applicants who do not meet the academic requirement can take the Pre-Masters Preparation Course at the University of Strathclyde International Study Centre (non-UK/Ireland students).

Domestic applicants: GBP 13,300 a year (2027/28). Full-time tuition per academic year. Same fee for Scottish and England, Wales & Northern Ireland students. Source

International applicants: GBP 28,500 a year (2027/28). Full-time tuition per academic year. Source

Intake: September

Duration: 12 months full-time (on campus)

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