Focuses on the principles and practice of AI and machine learning, from algorithms to applied projects. Open to graduates in related subjects and, with suitable supplementary experience, some from non-cognate backgrounds.
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Check your fitMatch your level, budget, intake and preferences.
Use these as an early planning guide. We will confirm the exact university rules for your qualification and intake before you apply.
01Academic route
Your qualification fit
Four-year Bachelor Special or Honours degree with CGPA 2.8/4 or 55%+; or three-year Bachelor General degree with CGPA 3.3/4 or 80%+; or a UK/Ireland/Australia-affiliated degree completed within the last five years
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Scholarship information
Potential funding at Liverpool John Moores University
Automatic international scholarships of £3,000 to £4,500 off tuition fees (course pages state up to £4,000) for eligible applicants; courses with fees under £17,250 are not eligible.
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 Artificial Intelligence and Machine Learning
Focuses on the principles and practice of AI and machine learning, from algorithms to applied projects. Open to graduates in related subjects and, with suitable supplementary experience, some from non-cognate backgrounds.
This 12-month postgraduate route concentrates on machine learning and intelligent systems, data, algorithms and model evaluation, responsible ai and real-world implementation. The course record does not promise a placement, so students should judge it primarily by its curriculum, teaching approach and project opportunities.
Course focus
What you can expect to explore
Machine learning and intelligent systems
Data, algorithms and model evaluation
Responsible AI and real-world implementation
Prepare, analyse and communicate insights from data.
Skills development
Capabilities you can build
Algorithmic problem-solving
Model development and testing
Programming with data
Responsible technology evaluation
The balance of technical, academic and professional skills depends on the modules and assessments offered for your intake.
Learning experience
How you may learn
Practical, laboratory, studio, simulation or supervised activities where appropriate to the discipline.
Independent postgraduate study, critical reading and a dissertation or major project where required.
Assessment may combine coursework, reports, presentations, examinations or projects; the exact balance is set by the university.
Who is this course for?
A strong fit for students with a strong interest in computation who want to design, evaluate and apply intelligent systems responsibly. 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:
AI or machine-learning specialist
Data scientist
Intelligent-systems developer
AI solutions consultant
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.
7 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.
01
Research Methods20 credits
02
Project Dissertation60 credits
03
Foundations of Machine Learning20 credits
04
Deep Learning Concepts and Techniques20 credits
05
Accelerated Machine Learning20 credits
06
Advanced Topics in Deep Learning20 credits
07
Enterprise Machine Learning20 credits
Entry requirements
Can I apply?
Academic
2:2 Bachelor's honours degree in a cognate subject, or in a non-cognate subject when supplemented by relevant experience
Sri Lankan qualifications
Four-year Bachelor Special or Honours degree with CGPA 2.8/4 or 55%+; or three-year Bachelor General degree with CGPA 3.3/4 or 80%+; or a UK/Ireland/Australia-affiliated degree completed within the last five years
English (IELTS)
6.0 overall, minimum 5.5 in each component
English alternatives
Sri Lankan O-Level English grade B or above accepted for programmes requiring IELTS 6.5, grade C or above for programmes requiring IELTS 6.0 (no expiry date)
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More Data Science & AI courses at Liverpool John Moores University
Course information checked October 2026 from the official course page on ljmu.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 Liverpool John Moores University before you apply. Global Educational Consultants is an independent consultancy.
MSc Artificial Intelligence and Machine Learning at Liverpool John Moores University | Fees & Entry | GEC