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University of Liverpool · Liverpool

BSc (Hons) Computer Science

UndergraduateComputing & ITPlacement year option

Covers computer science from core principles to current technologies, with specialist pathways such as AI, cyber security and data science. The programme develops programming, software development, computer systems, data and secure digital services. At undergraduate level, the course develops subject knowledge progressively alongside practical, analytical and transferable skills.

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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

Passes in three subjects in Sri Lankan or London A-levels at the grades required for the course (e.g. AAB–ABB); otherwise a Foundation Certificate at University of Liverpool International College

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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

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Scholarship information

Potential funding at University of Liverpool

High-achieving international master's students can receive a £7,000 tuition fee discount through the Liverpool Scholarships; awards also exist for undergraduates progressing from University of Liverpool International College.

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 BSc (Hons) Computer Science

Covers computer science from core principles to current technologies, with specialist pathways such as AI, cyber security and data science. The programme develops programming, software development, computer systems, data and secure digital services. At undergraduate level, the course develops subject knowledge progressively alongside practical, analytical and transferable skills.

This 36-month undergraduate route concentrates on data preparation, exploration and visualisation, statistical modelling and machine-learning methods, turning complex evidence into useful decisions. A placement or professional-experience option is recorded, which can help connect academic learning with workplace practice when available.

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

  • Applied work such as case studies, workshops, projects or problem-based tasks.
  • Independent study and progressively more complex assignments or projects.
  • A placement or professional-experience route is recorded; its length, availability and eligibility should be confirmed for the selected intake.
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.

36 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
    Foundations of Computer Science and Artificial Intelligence (compulsory)Module COMP131
  2. 02
    Foundations of Data Science (compulsory).Module COMP132
  3. 03
    INTRODUCTION TO PROGRAMMINGModule COMP101
  4. 04
    PROGRAMMING LANGUAGE PARADIGMSModule COMP105
  5. 05
    DESIGNING SYSTEMS FOR THE DIGITAL SOCIETYModule COMP107
  6. 06
    DATA STRUCTURES AND ALGORITHMSModule COMP108
  7. 07
    OBJECT-ORIENTED PROGRAMMINGModule COMP122
  8. 08
    Software Engineering in Practice (compulsory)Module COMP290
  9. 09
    Planning Your Career (optional)Module COMP291
  10. 10
    Computer Systems (optional)Module COMP286
  11. 11
    Web Programming Languages (optional)Module COMP288
  12. 12
    Systems Programming with C/C++ (optional).Module COMP287
  13. 13
    SOFTWARE ENGINEERING FUNDAMENTALSModule COMP201
  14. 14
    COMPLEXITY OF ALGORITHMSModule COMP202
  15. 15
    DATABASE DEVELOPMENTModule COMP207
  16. 16
    GROUP SOFTWARE PROJECTModule COMP208
  17. 17
    COMPUTER NETWORKSModule COMP211
  18. 18
    INTRODUCTION TO THEORY OF COMPUTATIONModule COMP218
  19. 19
    ADVANCED ARTIFICIAL INTELLIGENCEModule COMP219
  20. 20
    APP DEVELOPMENTModule COMP228
  21. 21
    CORE DATA SCIENCEModule COMP229
  22. 22
    PRINCIPLES OF COMPUTER GAMES DESIGN AND IMPLEMENTATIONModule COMP222
  23. 23
    COMPUTER-BASED TRADING IN FINANCIAL MARKETSModule COMP226
  24. 24
    CYBER SECURITYModule COMP232
  25. 25
    BECOMING ENTREPRENEURIALModule ULMS254
  26. 26
    HONOURS YEAR COMPUTER SCIENCE PROJECTModule COMP390
  27. 27
    KNOWLEDGE REPRESENTATION AND REASONINGModule COMP304
  28. 28
    ADVANCED SOFTWARE ENGINEERINGModule COMP319
  29. 29
    INTRODUCTION TO COMPUTATIONAL GAME THEORYModule COMP323
  30. 30
    HIGH PERFORMANCE COMPUTINGModule COMP328
  31. 31
    AUTONOMOUS MOBILE ROBOTICSModule COMP329
  32. 32
    OPTIMISATIONModule COMP331
  33. 33
    COMMUNICATING COMPUTER SCIENCEModule COMP335
  34. 34
    BIG DATA ANALYTICSModule COMP336
  35. 35
    COMPUTER VISIONModule COMP338
  36. 36
    QUANTUM COMPUTING AND SECURITYModule COMP345

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
A levels AAB
Sri Lankan qualifications
Passes in three subjects in Sri Lankan or London A-levels at the grades required for the course (e.g. AAB–ABB); otherwise a Foundation Certificate at University of Liverpool International College
English (IELTS)
6.0 overall, no component below 5.5

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How we help

Support, clearly agreed.

  1. We check your eligibility and documents.
  2. We prepare and submit your application to University of Liverpool.
  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 liverpool.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 Liverpool before you apply. Global Educational Consultants is an independent consultancy.