Your qualification fit
2:2 honours degree in any discipline with exposure to quantitative methods such as statistics
Check my qualifications →Lancaster University · Lancaster
MSc Data Science
Core study in statistics, Python programming, machine learning and AI, then a chosen pathway (Biodiversity, Business Intelligence or Data Engineering). Ends with a 14-week industry placement or dissertation, which suits career changers with some quantitative background.
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Use course matcher →Plan the full costTuition pre-filled, with GBP and indicative LKR totals.
Open budget planner →Funding informationThis university has scholarship information recorded.
Explore funding →Sri Lankan student planning
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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
6.5 overall, minimum 6.0 in each element
See English options →Scholarship possibilities
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 Lancaster University
Postgraduate scholarships listed on course pages include a Master's Excellence Scholarship (15% of tuition, based on grades), a £2,000 International Early Acceptance Scholarship, and a £10,000 Postgraduate International Regional Scholarship for eligible nationalities (eligibility of Sri Lanka not confirmed).
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 MSc Data Science
Core study in statistics, Python programming, machine learning and AI, then a chosen pathway (Biodiversity, Business Intelligence or Data Engineering). Ends with a 14-week industry placement or dissertation, which suits career changers with some quantitative background.
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.
24 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.
- 01Fundamentals of Data Science and Artificial IntelligencePublished course content
- 02Introduction to Artificial Intelligence and Data SciencePublished course content
- 03MSc DissertationPublished course content
- 04Requirements capturePublished course content
- 05Basic specificationPublished course content
- 06Literature reviewPublished course content
- 07Formulation of a detailed project planPublished course content
- 08Execution of methodsPublished course content
- 09Production of resultsPublished course content
- 10Writing a detailed discussionPublished course content
- 11Synthesising the overall dissertationPublished course content
- 12Presenting results to your academic supervisor and industry or research partnerPublished course content
- 13Statistical LearningPublished course content
- 14Advanced Topics in Artificial IntelligencePublished course content
- 15Intelligent Agents and Autonomous SystemsPublished course content
- 16Large Scale Platforms for AI and Data AnalysisPublished course content
- 17Natural Language Processing and Language ModelsPublished course content
- 18Simulation and Reinforcement LearningPublished course content
- 19Statistical EcologyPublished course content
- 20Applied Data Science for BiodiversityPublished course content
- 21Forecasting and Time-Series AnalyticsPublished course content
- 22GeoinformaticsPublished course content
- 23Machine Learning and Data MiningPublished course content
- 24Optimisation and HeuristicsPublished course content
Entry requirements
Can I apply?
- Academic
- 2:2 honours degree in any discipline with exposure to quantitative methods such as statistics
- Sri Lankan qualifications
- We’ll check your qualifications against this course for you.
- English (IELTS)
- 6.5 overall, minimum 6.0 in each element
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How we help
Support, clearly agreed.
- We check your eligibility and documents.
- We prepare and submit your application to Lancaster University.
- 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.
More Data Science & AI courses at Lancaster University
- MSc Artificial IntelligenceMaster's · 1 year · £30,000/yr
- BSc (Hons) Data ScienceUndergraduate · 3 years · £30,770/yr
Similar courses at other universities
Course information checked October 2026 from the official course page on lancaster.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 Lancaster University before you apply. Global Educational Consultants is an independent consultancy.