Course summary
Our MSc Advanced Data Science is designed for students with a degree that includes a significant mathematical component.
- gain advanced practical skills in data analysis and machine learning, processing of big data, predictive modelling and the use of statistical software packages R and Python
- understand the theory behind machine learning and other predictive algorithms
- become equipped with the necessary training to work as a statistician and data scientist in a broad range of fields such as health, insurance, finance and commerce
Modules
Throughout your studies, you will take 100 credits of compulsory taught modules, 20 credits of elective taught modules, and in the third (summer) term you'll also undertake your MSc Project (60 credits).
Assessment method
The form of assessment varies across modules. For most modules, the assessment involves both coursework and practical computer-based or written examinations.
Entry requirements
Minimum second-class (2:2) Honours degree or overseas equivalent* in a mathematical discipline. Prospective students with relevant experience or appropriate professional qualifications are also welcome to apply. *For Australia and Canada, normal degrees are accepted.
Fees and funding
Tuition fees
No fee information has been provided for this course
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .
Additional fee information
No additional fees or cost information has been supplied for this course, please contact the provider directly.
Provider information
University of Strathclyde
McCance Building
16 Richmond Street
Glasgow
G1 1XQ