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
- Core modules: *
- Optional modules: *
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 5.5. |
| Cambridge English Advanced | Cambridge English: Advanced (CAE) (taken after January 2015). An overall score of 169 with no component score less than 162. | |
| Cambridge English Proficiency | Cambridge English: Proficiency (CPE) (taken after January 2015). An overall score of 169 with no component score less than 162. | |
| PTE Academic | 62 | An overall score of 62 with a minimum of 59 in each skill. |
| TOEFL (iBT) | 79 | 79 with a minimum of 18 in Reading, 17 in Listening, 20 in Speaking and 17 in Writing. |
| Trinity ISE | Pass | Trinity College Integrated Skills in English (ISE) Level III with a Pass in all 4 components. |
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
**Postgraduate fees for 2026 entry will be available shortly.**
For further fee information please see the corresponding University of Portsmouth course page or visit https://www.port.ac.uk/study/masters-and-postgraduate-taught/fees-and-funding
Provider information
University of Portsmouth
University House
Winston Churchill Avenue
Portsmouth
PO1 2UP