UCL's MSc Data Science and Machine Learning is one of the university's most in-demand quantitative postgraduate degrees — a one-year, technically rigorous programme that sits alongside MSc Computer Science as one of UCL's flagship computing-adjacent master's, at a university ranked 8th globally (QS World University Rankings 2027) and based in central London, a few minutes from the offices of most major tech and finance employers who recruit this exact skill set. It's run out of UCL's computing and statistics ecosystem, drawing on the department's genuine research strength in machine learning. This guide covers what the programme actually costs, what UCL asks for, and how selective it realistically is.
Acceptance Rate: What We Actually Know
UCL publishes aggregate offer-rate data more transparently than Oxford or Cambridge, but it does not isolate a figure for MSc Data Science and Machine Learning specifically. Here's what's actually available:
| Level | Published Rate | Source |
|---|---|---|
| UCL undergraduate (all courses, university-wide) | 43.4% (recent aggregate offer rate) | UCL's own published admissions data |
| UCL postgraduate taught (all courses, university-wide) | 38% (recent aggregate offer rate) | UCL's own published admissions data |
| MSc Data Science and Machine Learning specifically | Not published | No departmental figure is released |
UCL states directly that its 38% postgraduate aggregate "masks enormous variation," with "some specialised MSc programmes run[ning] near 6-8%." Data Science and Machine Learning is a globally in-demand field, and a programme like this — combining UCL's computing and statistics strengths — is a realistic candidate for sitting toward that more selective end, given how competitive machine learning-focused master's degrees have become across UK and global universities generally. Treat 38% as a university-wide postgraduate baseline only, not a programme-specific estimate, and be skeptical of any source that quotes a precise MSc Data Science and Machine Learning percentage — none is published by UCL.
Tuition & Fees
UCL does not isolate a published tuition figure specifically for MSc Data Science and Machine Learning in the same way it does for MSc Computer Science, so this guide uses UCL's own representative postgraduate taught figures as the honest baseline — confirm the exact current course fee directly on UCL's programme page before budgeting.
| Item | Amount (USD, representative postgraduate figure) |
|---|---|
| Tuition (international/Overseas, representative) | ~$57,238/year (UCL's published 2026–27 Overseas range for taught master's runs from roughly GBP 26,200 up to GBP 57,700 depending on course) |
| Tuition (Home/UK, representative) | ~$28,810/year |
| Living expenses (representative UCL estimate) | ~$30,603/year |
| Estimated total cost of attendance | ~$87,841/year |
| Application fee | ~$121 (GBP 90 standard postgraduate taught fee) |
As a computationally intensive, high-demand quantitative programme, Data Science and Machine Learning is likely to sit toward the upper half of UCL's published Overseas fee range rather than at the low end — always check the specific course page. Figures are converted from GBP at roughly 1 GBP = 1.34 USD. On funding, the UCL Global Master's Scholarship (GBP 15,000 toward one year of study, for Overseas fee-status students demonstrating financial need) is a realistic option to apply for alongside faculty- and department-specific awards.
Admission Requirements
UCL does not use a GPA scale — it evaluates prior degree classification on a course-by-course basis. For MSc Data Science and Machine Learning specifically:
- Academic background: At least a UK upper-second-class (2:1) honours degree or recognised international equivalent, typically in Computer Science, Mathematics, Statistics, Engineering, Physics, or another strongly quantitative discipline — programmes of this kind generally expect demonstrated programming ability (commonly Python) alongside a solid mathematical/statistical foundation (linear algebra, probability, calculus).
- Documents required:
- Statement of purpose / personal statement
- Two academic (or academic plus professional) references
- Official transcripts from all previously attended institutions
- CV/résumé
- English language proficiency scores (unless exempt — see below)
- GRE/GMAT: not required for most UCL taught master's, including this programme. UCL's GRE requirement is limited to specific courses, most notably MSc Economics (GRE Quantitative 162 minimum) — Data Science and Machine Learning does not require it, though a strong quantitative profile still matters heavily in the academic review.
- Application fee: GBP 90 (~USD 121) for standard postgraduate taught courses.
- Deadlines: Rolling and department-specific; most taught master's open around October/November of the prior year and close once full. Given how competitive quantitative computing-adjacent programmes are at UCL, expect this course to fill well before any final published deadline, similar to UCL's Computer Science and Business School programmes.
How to Get In
- Apply as early in the cycle as possible. UCL's rolling admissions model means competitive quantitative programmes routinely close early once places fill, so a complete application in October/November is materially stronger positioning than one submitted in the spring.
- Lead with demonstrated technical and mathematical ability, not just a related degree title. For a programme combining data science and machine learning, admissions readers are looking for concrete evidence of statistical and programming competence — relevant coursework, projects, a portfolio (e.g. GitHub), or applied work experience involving real datasets.
- Make your personal statement specific about which side of the programme interests you most — data science's applied/statistical side or machine learning's more algorithmic/research side — and connect it to UCL's own research strengths where possible, rather than writing a generic "AI is the future" statement.
- Speaking is the section UCL flags most often as a weak spot for quantitative MSc applicants, particularly relevant for group project work and any interview stage — budget real practice time here even if your Reading/Listening scores come easily.
- If you're not from a pure computer science background (e.g. you're coming from physics, economics, or engineering with strong quantitative training), make the transferability of your quantitative skills explicit in your statement rather than assuming it's obvious from your transcript alone.
- Plan financing early, given the likely cost toward the upper end of UCL's published Overseas fee range — several UCL scholarships, including the Global Master's Scholarship, have their own separate application windows that should be started alongside your main application.
English Proficiency Requirement (IELTS/TOEFL)
UCL uses a five-level internal system for English requirements, and a demanding, research-adjacent quantitative programme like Data Science and Machine Learning may sit at UCL's Level 1 (Standard) or a higher level depending on current departmental policy — always confirm directly on the course page.
| Level | IELTS Overall | IELTS Per Component | TOEFL iBT Overall |
|---|---|---|---|
| Level 1 (Standard) | 6.5 | 6.0 minimum each | 92 |
| Level 2 (used by a number of more demanding departments) | 7.0 | 6.5 minimum each | 96–100 |
UCL also accepts PTE Academic (minimum 62) and Duolingo English Test (minimum 120), and offers conditional admission through its pre-sessional English programme for admitted students who narrowly miss the required score. For the complete breakdown by course and test type, see Gabble's dedicated guides: UCL IELTS requirements and UCL TOEFL requirements.
Career Outcomes
UCL publishes actual graduate-level employment data, which gives a useful (if university-wide rather than programme-specific) baseline for this programme:
| Metric | UCL Postgraduate (all courses) |
|---|---|
| Employment rate after 6 months | 87% |
| Average starting salary | ~$46,900 |
UCL's top postgraduate recruiters include the NHS, Deloitte, Amazon, Accenture, PwC, and KPMG. Data Science and Machine Learning graduates are particularly well positioned relative to this list, since Amazon and Accenture both actively recruit data science and ML talent, and the broader London finance and tech sector has strong, consistent demand for exactly this combination of statistical and machine learning skills. Given how in-demand this specific skill set is globally, it's reasonable to expect Data Science and Machine Learning graduates to perform at or above the university-wide average on both employment rate and starting salary, though UCL does not publish a figure broken out for this specific programme. Typical destinations include data scientist, machine learning engineer, and applied research roles across tech, finance, consulting, and increasingly healthcare and public sector data teams, plus a smaller share progressing to PhD study in machine learning or statistics.
FAQ
What is UCL's acceptance rate for MSc Data Science and Machine Learning? Not separately published. UCL's aggregate postgraduate taught offer rate is 38%, but UCL itself notes this figure "masks enormous variation," with specialised programmes running as low as 6-8%. Given how competitive data science and machine learning master's degrees are globally, expect the real figure for this programme to sit well below the 38% average.
How much does UCL's MSc Data Science and Machine Learning cost? UCL does not publish a course-isolated figure for this programme in this dataset; using UCL's representative postgraduate taught estimate (~$57,238/year tuition, ~$87,841/year total cost of attendance) is a reasonable starting point, but confirm the exact current fee on UCL's own course page, since it likely sits toward the upper half of UCL's published Overseas fee range given the programme's computational intensity.
Do I need the GRE or GMAT for this programme? No. UCL's GRE requirement is limited to specific courses, most notably MSc Economics. MSc Data Science and Machine Learning does not require either test, though strong quantitative credentials are still central to the academic review.
What IELTS or TOEFL score do I need? Likely UCL's Level 1 (Standard) requirement — IELTS 6.5 overall (6.0 minimum per component) or TOEFL 92 overall — though some demanding quantitative departments require UCL's higher levels, so confirm directly on the current course page.
What background do I need to apply — does it have to be a Computer Science degree? No. UCL typically welcomes applicants from Computer Science, Mathematics, Statistics, Engineering, Physics, and other strongly quantitative backgrounds, provided you can demonstrate solid programming ability and a mathematical/statistical foundation, ideally supported by relevant projects or coursework.
What are typical career outcomes for graduates of this programme? UCL's university-wide postgraduate employment rate is 87% after six months with an average starting salary of roughly $46,900 (not programme-specific). Given strong global demand for data science and machine learning skills, and recruiters like Amazon and Accenture on UCL's own top-recruiter list, graduates of this specific programme are reasonably likely to perform at or above that baseline.