Computational Statistics and Machine Learning MSc

1 Year On Campus Masters Program

University College London

Program Overview

Program overview:
This one-year Master’s programme brings together rigorous statistical modelling and modern machine learning techniques, offering you the tools to analyse, visualise and interpret complex data in a data-rich world. It’s ideal if you’re coming from a strong quantitative background and want to either step into industry roles in machine learning/statistics or build a research-oriented foundation.

Curriculum structure:
Year 1 (full-time, only year) – Term 1: You’ll begin with core modules like Supervised Learning and Statistical Models and Data Analysis, putting you deeply into the fundamentals of classical and contemporary supervised learning algorithms and statistical modelling of the exponential family of distributions. Alongside these you choose from optional topics that allow you to broaden your base.
Term 2: As you advance, you continue with optional and elective modules — for example Probabilistic and Unsupervised Learning, Graphical Models, Applied Deep Learning — where you deepen your understanding of unsupervised methods and graphical probabilistic frameworks, and you also start preparation for your major research project/dissertation.
Term 3: The final stretch centres around the MSc Computational Statistics and Machine Learning Project, where you undertake a substantial project (often in collaboration with industry or with an academic researcher) and consolidate your learning, putting theory into practice and generating an outcome you can show future employers or research teams.

Focus areas: “supervised learning, probabilistic and unsupervised models, statistical data analysis, deep learning, machine vision, graphical models, reinforcement learning”
Learning outcomes: “gain deep expertise in machine learning and computational statistics; develop advanced analytical, programming and modelling skills; be prepared for research or industry roles in machine learning/statistics; produce a substantial project demonstrating your capability”
Professional alignment (accreditation): While the page does not list a specific professional accreditation, it emphasises strong industry links (for example with DeepMind) and excellent employability outcomes.
Reputation (employability rankings): UCL is ranked 9th in the Quacquarelli Symonds World University Rankings 2026. Graduates from this programme have been hired at major tech and finance companies including Amazon, Microsoft and UBS

Experiential Learning (Research, Projects, Internships etc.)

Students build hands-on expertise in real statistical modelling, algorithm development and machine-learning systems, putting theory into practice from day one. The programme is delivered via a blend of lectures, tutorials, lab classes and self-directed work in one of the world’s leading research institutions. Within the department you’ll access powerful computing infrastructure and benefit from projects aligned with industry and research partners. Specifically, as part of UCL’s computer science and statistics ecosystem you’ll be joining a community of applied practitioners and researchers rather than only being in a lecture theatre. You’ll work with real data, write code, prototype solutions, and undertake a substantial project — all within a rich facility- and resource-driven environment.

Here’s how it plays out in practice:

Undertaking a substantial project/dissertation (60 credits) where you can work either with an academic researcher or an industry partner via UCL’s Industry Exchange Network.
Participating in lab classes and tutorials alongside lectures, supported by online resources and the department’s computing hardware for machine-learning tasks.
Accessing computing capability within the Computer Science department for machine-learning work — the programme explicitly notes you may want a capable GPU and that resources are available for computationally intensive projects.
Working on modules that span both statistics and machine learning (e.g., “Statistical Models and Data Analysis”, “Supervised Learning”, “Applied Machine Learning”, “Bayesian Deep Learning”) — giving you hands-on exposure across methods and models.
Engaging with industry-embedded research and guest or collaborative modules (for example alongside the Gatsby Computational Neuroscience Unit and Google DeepMind) — which helps tie your technical learning to cutting-edge applications.
Being part of UCL’s broader facilities: a rich specialist library system, clusters of high-performance machines and study spaces embedded in a top-ranked research environment.

Progression & Future Opportunities

With this MSc you’ll be ready to step into industry or research with confidence:

University services to help you employ: You’ll have full access to the UCL Careers service for one-to-one career consultations, CV and interview preparation, and job/internship listings.
Employment stats and salary figures: For UCL postgraduate taught programmes, the median starting salary is reported around £35,000 for full-time graduates. Meanwhile for the UCL Computer Science MSc programmes data show a median salary around £45,000 and highly skilled work/further study rate of ~95% 15 months after graduation.
University–industry partnerships: This MSc features teaching alongside the Gatsby Computational Neuroscience Unit and Google DeepMind, giving you exposure to top-tier industry research. Also, projects are undertaken in collaboration with industry partners via UCL’s industry-exchange network.
Long-term accreditation value: UCL is consistently ranked among the world’s top universities and its Computer Science department is recognised for research excellence (ranked first in England for research power). A qualification from UCL carries strong international credibility.
Graduation outcomes: Graduates from this programme have gone on to companies such as Amazon, Apple, Microsoft, UBS and more; others pursue further study at institutions like University of Cambridge or back at UCL.

Further Academic Progression:
If you finish the MSc and want to go further, you’re in a strong position to:

Launch into a PhD in Machine Learning, Statistics, Artificial Intelligence or Data Science at UCL or another top institution.
Or specialise further via a postgraduate certificate/diploma or advanced research-based programme in sub-fields such as Deep Learning, Natural Language Processing, Reinforcement Learning, or Computational Neuroscience.