Course summary
Overview Master big data methodologies and find the valuable trends and patterns buried in complex datasets with our MSc Data Analytics course. You'll build your proficiency with data mining tools, unlock specialist knowledge of professional analysis methods, and apply your learning to real data drawn from professional partners, such IBM, or from live University research into cosmology, health informatics and cybersecurity. You'll plan and produce an in-depth research project, using analytics packages like Hadoop and Tableau, and we'll provide the expertise and support so you can develop your professional practice. And once you graduate, you'll have a skillset that'll get you noticed – and all the tools you need to progress your career in data analytics or deep learning. What you'll experience On this course you'll:
- Plan and deliver your Master's project in collaboration with an industry partner – previous projects have analysed data from Fresh Relevance, Specsavers and IBM to support strategic priorities
- Build your own database from complicated, real-world datasets, and apply robust statistical methods to produce actionable, data-driven insights
- Use industry-standard software, such as Knime, Tableau, Hadoop and Spark, and engage with modern techniques including machine learning, AI, and Business Intelligence Modeling
- Convert your existing study or workplace knowledge into a the necessary skillset for modern data-driven careers
- Senior data scientist
- Data architect
- Data officer
- Information strategist
- PhD research
Modules
What you'll study on this MSc Data Analytics degree course Each module on this course is worth a certain number of credits. You need to study modules worth a total of 180 credits. For example, 4 module worth 30 credits and 1 module worth 60 credits. Core modules include:
- Big Data and Machine Learning Applications (30 credits)
- Data Management (15 credits)
- Data Visualisation and Exploratory Analytics (15 credits)
- Intelligent Data and Text Analytics (30 credits)
- Masters Project (60 credits)
- Programming for Data Analytics and AI (15 credits)
- Business Intelligence (15 credits)
- Cyber Security for Information Systems (15 credits)
- Explainable AI (15 credits)
- Statistical Machine Learning (15 credits)
Assessment method
You will encounter a range of assessment styles depending on the content and nature of the unit topic. This can include written assignments and presentations, as well as group and individual lab-based assessments. However, the most significant assessment element is your project.
Professional bodies
Professionally accredited courses provide industry-wide recognition of the quality of your qualification.
- British Computer Society
Entry requirements
A second-class honours degree in a relevant subject, or equivalent professional experience and/or qualifications.
English language requirements
| Test | Grade | Additional details |
|---|---|---|
| IELTS (Academic) | 6 | English language proficiency at a minimum of IELTS band 6.0 with no component score below 6.0. |
| Cambridge English Advanced | Cambridge English: Advanced (CAE) taken after January 2015. An overall score of 176 with no component score less than 169. | |
| Cambridge English Proficiency | Cambridge English: Proficiency (CPE) taken after January 2015. An overall score of 176 with no component score less than 169. | |
| TOEFL (iBT) | 79 | 79 with a minimum of 20 in Reading, 19 in Listening, 21 in Speaking and 20 in Writing. |
| PTE Academic | 54 | An overall score of 54 with a minimum of 54 in each skill. |
Fees and funding
Tuition fees
| EU | £10400 | Year 1 |
| England | £10400 | Year 1 |
| Northern Ireland | £10400 | Year 1 |
| Scotland | £10400 | Year 1 |
| Wales | £10400 | Year 1 |
| Channel Islands | £10400 | Year 1 |
| Republic of Ireland | £10400 | Year 1 |
| International | £19200 | Year 1 |
Additional fee information
Students who are resident in EU countries: please note that the net fee is inclusive of the Transition Scholarship
Fees are accurate at the time of publishing and are subject to change at any time without notice.
Fees may also go up in later years, in line with inflation.
Provider information
University of Portsmouth
University House
Winston Churchill Avenue
Portsmouth
PO1 2UP