Skip to main content

Advanced Machine Learning MSc

1 year, starting in September 2025

Prepare for a career in machine learning with specialist skills and knowledge in designing, developing, and deploying machine learning systems.

Machine learning is changing modern society, transforming industries such as healthcare, finance, and even entertainment. The landscape of machine learning is rapidly evolving, with new developments paving the way for increasingly innovative technological applications.

This course provides you with the advanced knowledge and skills needed to design, develop and deploy machine learning systems. You will learn about the fundamental concepts of machine learning, such as supervised learning, as well as a range of baseline machine learning algorithms, including linear and logistic regression, support vector machines and decision trees. You will also gain an understanding of cutting-edge methodologies, preparing you for a career in a variety of industries, including healthcare, autonomous vehicles, finance, natural language processing and computer vision.

To ensure you’re well-prepared to excel in advanced machine learning studies and research, you will need a strong first degree in a numerate subject such as computer science, mathematics, physics, or engineering. You should also be able to demonstrate proficiency in mathematical topics such as calculus and linear algebra, possess some familiarity with probability and statistics, and have a solid foundation in programming, particularly in Python.

Register your details to watch our short taster lectures and get a taste of the high-quality teaching on our AI courses.

Course highlights

  • Gain a deep understanding of the theoretical foundations of machine learning and hands-on experience in deploying machine learning systems using current development tools, core software libraries and cloud-based delivery technologies.
  • Specialised knowledge and skills in advanced topics such as computer vision, natural language processing, reinforcement learning, and robotics.
  • Exposure to the latest research and technology in machine learning, including exploring how new innovations are shaping the field.
  • Collaborate on team projects where students will present their work to peers and instructors.
  • Be part of our supportive postgraduate community.
  • Live and study in a beautiful world heritage city.

Specialist facilities

You will have access to purpose-built teaching labs, including a maker lab, allowing you to explore, create, experiment and share software-driven and physical artefact projects in a collaborative workspace context. Complex, data-intensive processes can be analysed over our in-house GPU Cluster. You will have access to most of our specialist labs 24/7.

Research project

During the summer, you will carry out a research project in fundamental or applied artificial intelligence. Through your project, you’ll propose, contextualise, perform, and critically evaluate your research, and disseminate the results to an expert audience.

Career prospects

After graduating, you'll be well-placed for a variety of careers in industry. Throughout your studies, you will have access to a development programme via timetabled sessions and that includes employer events which will raise your awareness of the commercial opportunities available to a technologist.

Alongside the specialist skills and knowledge you'll gain, our dedicated careers team offers individual guidance and helps you decide between employment and further study.

Find out more on maximising your employability while at Bath.

Find out more about studying at Bath

2025/26 Academic Year


Before you apply for a course, please check the website for the most recently published course detail. If you apply to the University of Bath, you will be advised of any significant changes to the advertised programme, in accordance with our Terms and Conditions.

We understand that you will want to know more about the shape of the academic year. We work hard and plan for different scenarios, to be able to welcome you to the University of Bath at the start of each semester.

Course structure

This course lasts 1 year. It starts in September 2025 and ends in 2026. Welcome week starts on 22 September 2025.


Occasionally we make changes to our programmes in response to, for example, feedback from students, developments in research and the field of studies, and the requirements of accrediting bodies. You will be advised of any significant changes to the advertised programme, in accordance with our Terms and Conditions.

Year 1

Semester 1

Compulsory units

  • Applied machine learning

    10 credits

  • Foundational machine learning

    10 credits

  • Operational software technologies

    5 credits

  • Reinforcement learning 1

    5 credits

  • Understanding deep learning

    10 credits

Semester 2

Alongside compulsory units, in semester 2, you will choose 10 credits of optional units. These could include topics such as natural language processing, reinforcement learning, computer vision, Bayesian machine learning, human and intelligent machines, and entrepreneurship.

Compulsory units

  • Applied machine learning

    Continued

  • Foundational machine learning

    Continued

  • Frontiers of machine learning

    5 credits

  • Research and development project skills

    5 credits

Summer

Compulsory units

  • Specialist project

    30 credits

Placement


This is the one-year version of the course without placement. We also offer this course with a placement year, giving you the opportunity to gain work experience as part of your degree.

Learning and assessment

You’ll be taught and assessed by a variety of methods and it will vary between units. These methods are designed to promote in-depth learning and understanding of the subject.


Learning

  • Laboratory sessions
  • Lectures
  • Seminars
  • Tutorials

Assessment

  • Dissertation
  • Essay
  • Presentations
  • Report
  • Written examination

These lists are to give you an idea of some, but not all, of the learning and assessment methods used on this course. They are not exhaustive lists and methods are subject to change.

Learning and teaching

Overall workload

You should expect to spend approximately 35 to 40 hours a week studying on your course. These hours consist of structured activities and independent learning. You will experience a mix of in person teaching, that will take place on campus, and structured online learning delivered through the University’s virtual learning environment.

Structured learning activities

MSc programmes deliver taught unit/modules in the first and second semester, with the Summer dedicated to a dissertation. The second semester will have less structured learning as you will start to prepare for your dissertation. Both during the dissertation preparation and the dissertation, supervision will take place at times suitable to you and your supervisor.

You can expect to spend between 9 to 18 hours engaged in structured learning activities per week, of which the majority will be in timetabled sessions on campus, and the remainder online.

In-person teaching and online activities

Timetabled sessions delivered in person on campus will be a mix of lectures, seminars, tutorials, and laboratories. Online activities may include following a recorded lecture, or other learning materials, or joining a timetabled live interactive session through Microsoft Teams or Zoom.

Independent learning

The remainder of your time outside these structured activities will be spent in independent learning which includes individual research, reading journal articles and books, working on individual and group projects, preparing coursework assignments, presentations, or revising for exams.

To support you in your studies you will be able to access, outside of timetabled learning, facilities on campus and in Bath such as study spaces, computers, and the Library.

Professional accreditations

Our courses have been accredited by the British Computer Society (BCS) for more than 30 years.


Recognition of professional qualifications


As well as being recognised as a higher academic qualification, a number of our degrees are also accredited by professional bodies in the United Kingdom. An accredited degree may entitle you to work in a specific profession within the UK, and abroad (where there are reciprocating arrangements with professional bodies in other countries).

The requirements to practise a profession vary from country to country. If you wish to practise your profession outside the United Kingdom, you are advised to confirm that the UK professional qualification you seek is valid in the country in which you are intending to work.

‘This course teaches you to use some of the most sophisticated tools and gives you the flexibility to study the very latest in key ideas.’
Prof. Mike Tipping Professor of Machine Learning

Entry requirements


Origin of qualifications

British qualifications

You should have a first or strong second-class Bachelor’s honours degree or international equivalent.

To apply for this course you should have an undergraduate degree in a numerate subject such as computer science, mathematics, physics, or engineering. You should also be able to demonstrate proficiency in mathematical topics such as calculus and linear algebra, possess a good knowledge of probability and statistics, and have a solid foundation in programming, particularly in Python.

We may make an offer based on a lower grade if you can provide evidence of your suitability for the degree.

If your first language is not English but within the last 2 years you completed your degree in the UK you may be exempt from our English language requirements.

English language requirements

  • IELTS: 6.5 overall with no less than 6.0 in all components
  • The Pearson Test of English Academic (PTE Academic): 62 with no less than 59 in any element
  • TOEFL IBT: 90 overall with a minimum 21 in all 4 components

You will need to get your English language qualification within 24 months prior to starting your course.

If you need to improve your English language skills before starting your studies, you may be able to take a pre-sessional course to reach the required level.

Fees and funding

Fees and funding information for Advanced Machine Learning MSc


Fees

Your tuition fees and how you pay them will depend on whether you are a Home or Overseas student.

Learn how we decide fee status

Tuition fees

See the most recent fees for postgraduate courses.

Placement fees

You will normally pay a reduced tuition fee while on a placement period or studying abroad. Find out more about placement fees and study abroad fees.

Extra costs

If you receive an offer, you will need to pay a non-refundable deposit of £1,000 when you accept to secure your place. This will be deducted from your tuition fee when you register.

IT requirements

For your course you will also need a desktop or laptop computer running relatively recent versions of either Windows, Mac or Linux operating system. Windows 10, MacOS Monterey or Ubuntu 22.04 LTS are recommended.

How to pay

Tuition fee loans

If you are studying a postgraduate course, you may be able to take out a loan for your tuition fees and living costs.

Read more about tuition fee loans

Scholarships and bursaries

You could be considered for a bursary or scholarship to help you study at Bath. You do not have to pay it back.

Read more about bursaries and scholarships

Other payment options

You can pay your tuition fees by Direct Debit, debit card, credit card or bank transfer. You may also be eligible for a student loan to help you pay your fees.

Read more about your payment options

Budgeting

You will need to budget at least £100 for the cost of photocopying, printing and binding. You will also need to budget for the cost of textbooks.

Some courses involve visits away from campus and you may be required to pay some or all of the costs of travel, accommodation and food and drink.

If you’re on a placement, you’re responsible for your own travel, accommodation and living costs. You should also consider the financial implications if you go on an unpaid or overseas placement.

Application information


  • Course title
    Advanced Machine Learning
  • Final award
    MSc
  • Mode of study
    Full-time
  • Department
  • Location
    University of Bath
    Claverton Down, Bath BA2 7AY
  • Home application deadline
    31 August 2025

    We recommend you apply early as we may close applications before the deadline if a course is full.

  • Overseas application deadline
    31 July 2025

    We recommend you apply early as we may close applications before the deadline if a course is full. We may consider late applications but if you need a Student Visa to study in the UK, you will need time to apply for and receive your visa to be in the UK by the start of the course.

  • Application eligibility
    Home and Overseas students are eligible to apply
  • Regulator

Course enquiries