Program Overview

Introduction to the Machine Learning MSc Program

The Machine Learning MSc program at University College London (UCL) is a highly esteemed and well-established master's program in the field of machine learning. This program offers specialization opportunities, including modules run in collaboration with the Gatsby Computational Neuroscience Unit and Google DeepMind. Taught at UCL, which is world-renowned for computer science research and breakthroughs, this program provides an exceptional environment to build expertise in this transformative field.

Program Details

• Study Mode: Full-time
• Duration: 1 calendar year
• Programme Start: September 2026
• Tuition Fees (2026/27):
  • UK students: ｣21,500
  • Overseas students: ｣42,700

Entry Requirements

To be eligible for the Machine Learning MSc program, applicants must have:

• A minimum of an upper second-class UK Bachelor's degree (or an international qualification of an equivalent standard) in a highly quantitative subject such as computer science, mathematics, electrical engineering, or the physical sciences.
• Relevant work experience may also be considered.
• Applicants must be comfortable with undergraduate mathematics in areas such as linear algebra and calculus.

English Language Requirements

The English language level for this course is Level 2. UCL Pre-Master's and Pre-sessional English courses are available for international students aiming to study for a postgraduate degree at UCL. These courses develop academic English and academic skills required to succeed at the postgraduate level.

Equivalent Qualifications

Country-specific information, including details of when UCL representatives are visiting different parts of the world, can be obtained from the International Students website. International applicants can find out the equivalent qualification for their country by selecting from a list of countries. The equivalency corresponds to the broad UK degree classification stated on the program page.

About the Degree

Machine learning is redefining intelligence and revolutionizing industries at an unprecedented pace. This Master's program positions students at the forefront of these changes, providing a robust foundation in machine learning principles and applications. Students benefit from UCL's expertise, studying a range of foundational and specialized modules, some taught in collaboration with leading organizations.

Who This Course Is For

This program is ideal for those aiming to start a career in research, development, or industries where machine learning is applied or emerging, such as finance, retail, pharmaceuticals, and computer security.

What This Course Will Give You

• Recognition from a Top-Ranked University: UCL is consistently ranked among the best universities globally.
• High-Quality Education: Learn from world-renowned academics at the forefront of computer science innovation.
• Real-World Experience: Apply knowledge and skills in practical settings with a substantial research project, often in collaboration with industry partners.
• Strong Employability: Graduates are highly sought after in the job market, with high employment rates and starting salaries.
• Enhanced Research Skills: Prepare for potential doctoral studies or research-intensive roles in industry.

Employability

This program focuses on both theoretical and practical aspects of machine learning, preparing students for roles in various industries or for PhD research. Graduates gain comprehensive knowledge to advance their careers rapidly.

Networking Opportunities

Students have regular opportunities to connect, collaborate, and network with peers and members of academia and industry, particularly through collaborative project work and research seminars. Access to the UCL Careers events program connects students with employers and alumni, providing invaluable insights into different roles, sectors, and application processes.

Teaching and Learning

The program is delivered through a combination of lectures, tutorials, and lab classes, supported by online resources. Assessment methods include coursework, projects, exams, and a final research project/dissertation. Full-time students typically have 12-16 contact hours per teaching week, with significant self-directed study and assessments totaling approximately 20-25 hours per week.

Modules

• Compulsory Modules:
  • Supervised Learning
  • MSc Machine Learning Project
• Optional Modules:
  • Graphical Models
  • Probabilistic and Unsupervised Learning
  • Open-Endedness and General Intelligence
  • Applied Machine Learning
  • Advanced Topics in Machine Learning
  • Approximate Inference and Learning in Probabilistic Models
  • Statistical Natural Language Processing
  • Reinforcement Learning
  • Machine Vision
  • Machine Learning Seminar
  • Bayesian Deep Learning
  • Applied Deep Learning

Accessibility

The department endeavors to make reasonable adjustments for students with disabilities. Details of the accessibility of UCL buildings can be obtained from AccessAble. Further information about support available can be obtained from UCL Student Support and Wellbeing Services.

Location

UCL Computer Science boasts state-of-the-art facilities designed to enhance the learning experience. The recently renovated labs and the Intelligent Robotics Lab at UCL East provide an optimal study environment. UCL also features an award-winning Student Centre and 18 specialist libraries.

Fees and Funding

• Tuition Fees: As mentioned earlier, ｣21,500 for UK students and ｣42,700 for overseas students for the 2026/27 academic year.
• Additional Costs: Students will require a modern computer with minimum specifications. The cost of living in London and additional expenses such as travel cards are also considerations.
• Funding Opportunities: Information about funding opportunities for UCL Computer Science taught postgraduate programs can be found on the department's scholarships webpage. A comprehensive list of funding opportunities available at UCL, including those relevant to nationality, can be found on the Scholarships and Funding website.