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University of Reading · Reading

MSc Applied Artificial Intelligence for Business

Master'sData Science & AI

A Henley Business School course on designing AI-driven business solutions, using data science tools, algorithms and cloud platforms, and assessing responsible AI adoption, with a research project. Open to graduates from any discipline.

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Funding informationThis university has scholarship information recorded.

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Sri Lankan student planning

Four checks before you shortlist this course.

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

Bachelor's degree (Special, Professional or Honours) with grade average from Second Lower / GPA 3.0 / B to Second Upper / GPA 3.3 / B+ depending on course

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03Funding

Scholarship possibilities

Scholarship or tuition-discount information is recorded for this university; eligibility may depend on course and intake.

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04Full financial plan

Beyond the tuition fee

Plan for tuition, visa fee, Immigration Health Surcharge, required maintenance funds, travel and your first accommodation costs.

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Free preliminary check

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This tool is an early planning guide, not an offer, admissions decision or visa assessment. The university decides admission after reviewing your complete application.

Scholarship information

Potential funding at University of Reading

Master's Excellence Scholarships of £4,000–£10,000 off tuition for 2027/28 international masters students (automatic, merit-based); Global Sustainability Leaders Scholarship of £6,000 a year towards living costs for undergraduates; £5,000 International Foundation Excellence Scholarship.

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 Applied Artificial Intelligence for Business

A Henley Business School course on designing AI-driven business solutions, using data science tools, algorithms and cloud platforms, and assessing responsible AI adoption, with a research project. Open to graduates from any discipline.

This 12-month postgraduate route concentrates on data preparation, exploration and visualisation, statistical modelling and machine-learning methods, turning complex evidence into useful decisions. 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

  • Data preparation, exploration and visualisation
  • Statistical modelling and machine-learning methods
  • Turning complex evidence into useful decisions
  • Machine learning and intelligent systems

Skills development

Capabilities you can build

  • Python or analytical programming
  • Statistical reasoning
  • Data visualisation
  • Model evaluation and communication

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 who enjoy combining programming, statistics and problem-solving to extract meaning from complex data. 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:

  • Data scientist
  • Data analyst
  • Business intelligence analyst
  • Machine-learning or analytics specialist

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.

26 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.

  1. 01
    Alumni supportPublished course content
  2. 02
    More infoPublished course content
  3. 03
    AI and Data Analytics in Business (INMR81)Published course content
  4. 04
    Academic authors Professor Keiichi NakataPublished course content
  5. 05
    AI Software on the Cloud (CSMASC)Published course content
  6. 06
    Fundamentals of Artificial Intelligence (CSMFAI)Published course content
  7. 07
    Business Data Analytics (INMR95)Published course content
  8. 08
    Academic authors Dr Markos KyritsisPublished course content
  9. 09
    Business Informatics (INMR91)Published course content
  10. 10
    Academic authors Professor Kecheng LiuPublished course content
  11. 11
    MSc Dissertation (Applied AI for Business) (INMR78)Published course content
  12. 12
    Academic authors Dr Stephen R GulliverPublished course content
  13. 13
    Problem Solving with Python (CSMPSP)Published course content
  14. 14
    Data Integration and Information Visualisation (CSMDIV)Published course content
  15. 15
    IT Project Management (INMR65)Published course content
  16. 16
    Academic authors Professor Yinshan TangPublished course content
  17. 17
    Digital and Sustainable Supply Chain Management (INMR08)Published course content
  18. 18
    Academic authors Dr Ajeseun JimoPublished course content
  19. 19
    A holistic approachPublished course content
  20. 20
    Ongoing supportPublished course content
  21. 21
    Boost your business English whilst you studyPublished course content
  22. 22
    International Study and Language Institute (ISLI)Published course content
  23. 23
    Speak clearly in meetings, presentations and group settingsPublished course content
  24. 24
    Write professionally for business, everything from emails to reports writingPublished course content
  25. 25
    Learn industry-specific terminologyPublished course content
  26. 26
    Prepare for your career with confident communication for interviews and networkingPublished course content

Source checked 19 October 2026. Titles are shown as concise factual course information; the university remains the authoritative source.

View official course contents

Entry requirements

Can I apply?

Academic
Good second class degree or equivalent in any discipline
Sri Lankan qualifications
Bachelor's degree (Special, Professional or Honours) with grade average from Second Lower / GPA 3.0 / B to Second Upper / GPA 3.3 / B+ depending on course
English (IELTS)
6.5 overall, no component below 5.5

Not sure you qualify? Send us your results — we’ll tell you honestly, free.

How we help

Support, clearly agreed.

  1. We check your eligibility and documents.
  2. We prepare and submit your application to University of Reading.
  3. We help you meet any offer conditions and get your CAS.
  4. We guide your Student visa application.

Your initial consultation is free. Any paid professional support begins only after you receive and accept a written service summary explaining the work, fee and terms.

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Course information checked October 2026 from the official course page on henley.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 University of Reading before you apply. Global Educational Consultants is an independent consultancy.