Your qualification fit
Bachelor's Special degree with at least lower second-class honours, depending on the course
Check my qualifications →University of Sussex · Brighton
Data Science MSc
Teaches statistical modelling, machine learning and programming tools for analysing large datasets, with an industrial placement-year option. For science, engineering and computing graduates heading into data-driven careers.
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Use these as an early planning guide. We will confirm the exact university rules for your qualification and intake before you apply.
IELTS or an alternative
6.0 overall, at least 5.5 in each component
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Scholarship or tuition-discount information is recorded for this university; eligibility may depend on course and intake.
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Scholarship information
Potential funding at University of Sussex
For 2026/27 Sri Lankan students are eligible for faculty awards and can apply for the Chancellor's International Scholarship; a Chancellor's Masters Scholarship is also listed. Amounts were not stated on the pages checked.
Eligibility, value, availability and deadlines are decided by the university. Confirm the award for this exact course and intake before relying on it.Programme overview
A clearer look at Data Science MSc
Teaches statistical modelling, machine learning and programming tools for analysing large datasets, with an industrial placement-year option. For science, engineering and computing graduates heading into data-driven careers.
This 12-month postgraduate route concentrates on data preparation, exploration and visualisation, statistical modelling and machine-learning methods, turning complex evidence into useful decisions. A placement or professional-experience option is recorded, which can help connect academic learning with workplace practice when available.
Course focus
What you can expect to explore
- Data preparation, exploration and visualisation
- Statistical modelling and machine-learning methods
- Turning complex evidence into useful decisions
- Machine learning and intelligent systems
Skills development
Capabilities you can build
- Python or analytical programming
- Statistical reasoning
- Data visualisation
- Model evaluation and communication
The balance of technical, academic and professional skills depends on the modules and assessments offered for your intake.
Learning experience
How you may learn
- Applied work such as case studies, workshops, projects or problem-based tasks.
- Independent postgraduate study, critical reading and a dissertation or major project where required.
- A placement or professional-experience route is recorded; its length, availability and eligibility should be confirmed for the selected intake.
Who is this course for?
A strong fit for students who enjoy combining programming, statistics and problem-solving to extract meaning from complex data. Entry requirements still determine eligibility, and students should compare the official module list with their own career goals before applying.
Career direction
Where it may lead
Relevant career directions may include:
- Data scientist
- Data analyst
- Business intelligence analyst
- Machine-learning or analytics specialist
These are examples, not guaranteed outcomes. Employment depends on your experience, location, professional registration where applicable and the modules completed.
Course contents
Published course content for this programme.
29 curriculum items were captured from the university’s official course page. These may include modules, course units or published curriculum topics, and can change by intake, pathway and availability.
- 01Guide to Masters studyPublished course content
- 02All yearPublished course content
- 03Dissertation (Data Science)Published course content
- 04Algorithmic Data SciencePublished course content
- 05Data Science Research Methods Autumn (L7)Published course content
- 06Data Science Masters Research ProposalPublished course content
- 07Machine LearningPublished course content
- 08Wider Topics in Data Science (L7)Published course content
- 09Advanced Methods in Molecular ResearchPublished course content
- 10Algorithmic Approaches to MathematicsPublished course content
- 11Applied Natural Language ProcessingPublished course content
- 12Applied Numerical Analysis (L.7)Published course content
- 13Data Analysis TechniquesPublished course content
- 14Linear Statistical Models (L7)Published course content
- 15Programming through PythonPublished course content
- 16Advanced Natural Language ProcessingPublished course content
- 17Image ProcessingPublished course content
- 18Machine Learning and Statistics for Health (L7)Published course content
- 19Monte Carlo Simulations (L7)Published course content
- 20Network SciencePublished course content
- 21Statistical Inference (L.7)Published course content
- 22Wearable TechnologiesPublished course content
- 23Web Applications and ServicesPublished course content
- 24Spirit of Sussex AwardPublished course content
- 25Video transcriptPublished course content
- 26Back to Course menuPublished course content
- 27Prof Luc BerthouzePublished course content
- 28Prof Jonathan LovedayPublished course content
- 29Prof George ParisisPublished course content
Entry requirements
Can I apply?
- Academic
- Upper second-class (2:1) honours degree in physics, engineering, science, computing, mathematics or life sciences
- Sri Lankan qualifications
- Bachelor's Special degree with at least lower second-class honours, depending on the course
- English (IELTS)
- 6.0 overall, at least 5.5 in each component
- English alternatives
- Standard IELTS 6.0 overall with 5.5 in each component
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How we help
Support, clearly agreed.
- We check your eligibility and documents.
- We prepare and submit your application to University of Sussex.
- We help you meet any offer conditions and get your CAS.
- We guide your Student visa application.
Your initial consultation is free. Any paid professional support begins only after you receive and accept a written service summary explaining the work, fee and terms.
Similar courses at other universities
Course information checked October 2026 from the official course page on sussex.ac.uk. The expanded description is original GEC guidance built from the recorded course summary, award level and subject; it does not reproduce a university or partner listing word for word. Exact modules, teaching, assessment, professional recognition, fees, entry requirements and intakes can change. We confirm the latest details with University of Sussex before you apply. Global Educational Consultants is an independent consultancy.