Manchester Metropolitan University

Data Science

This course is suitable for numerate graduates across many disciplines. Non-computing graduates are eligible. You will learn how to use state-of-the-art computer science methods to process a range of data, including (but not limited to) big data. You will develop technical, statistical, analytical and data mining skills. The course incorporates methods of statistical analysis and data mining to extract understanding from data, formulate high-quality data models and interpret them to 'tell a story'. You will learn how to communicate these effectively to stakeholders, bearing in mind ethical, legal and societal implications. You will be introduced to data science concepts, techniques and algorithms for processing and visualising datasets so as to infer useful, actionable knowledge. Features and benefits of the course - The School has an extensive range of equipment in our own specialist laboratories which is supported by a dedicated team of technical staff. - Research in the School was rated 'internationally excellent' with some rated 'world-leading' in the 2014 Research Excellence Framework (REF). - Our online virtual learning platform Moodle, provides access to lectures, course materials and assessment information. - Classes are concentrated on certain days of the week to facilitate part-time students' attendance and allow full-time students to undertake part-time employment if necessary. - The School of Computing, Mathematics and Digital Technology is a member of the Oracle Academy. - We are an academic partner of the Institute of Information Security Professionals (IISP). This partner status recognises our expertise in the field of information and cyber security. - We are also an Academy of the Computer Technology Industry Association (CompTIA) and deliver their partner programme which provides a pathway for students towards a rewarding, high-growth IT career.

Entry requirements

ou will normally have at least a second-class UK Honours degree (or international equivalent) in a STEM (Science, Technology, Engineering, Mathematics) or numerate subject area. Exceptionally, a good sub-degree STEM qualification and very substantial work experience in a closely-related area is acceptable.

Assessment methods

Assessment will be through coursework, examination and dissertation.


Qualification Study mode Start month Fee Course duration
MSc Full-time September 2017 - 1 Years
MSc Part-time September 2017 GBP 4,350 per Year 1 (Channel Islands) 2 Years
MSc Part-time September 2017 GBP 4,350 per Year 1 (International) 2 Years
MSc Part-time September 2017 GBP 2,520 per Year 1 (Home/EU) 2 Years
MSc Full-time September 2018 - 1 Years

Campus details

Campus name Town Postcode Region Main campus Campus Partner
Main Site M15 6BH North West

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