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Study MSc Data Science

Fees, Modules, Entry Requirements & Application for Bangladeshi Students

Quick View

  • Study Option
    Full-Time
  • Intakes
    February, September
  • Location
    Treforest Campus, Pontypridd, United Kingdom
  • Duration
    13 Months
  • Level
  • Subject
  • International Fees
    £ 16,900 per year
    Up to £ 8,000 scholarships
    Deposits: 50% of first-year tuition fees.

How to Apply

Before making an application, you will need to decide on your course and learn requirements clearly. Information in this page is available for the international students only.

Apply Now

The MSc Data Science at the University of South Wales is a full-time 13 Months Postgraduate program in the field of Computing & Cybersecurity. Delivered at the University's Treforest Campus campus in Pontypridd, United Kingdom, the course offers a balanced mix of academic study and practical experience.

Ideal for Bangladeshi students and other international applicants, this program provides high-quality education at a yearly competitive international tuition fee of £ 16,900 Starting each February, September, it is designed to equip students with essential skills for advanced study and professional growth.

The University of South Wales offers modern facilities and a supportive environment, ensuring international students receive the guidance and resources needed for success. With a welcoming campus community and dedicated support services, Bangladeshi students can confidently plan their study abroad journey in the United Kingdom through this program.

Course Highlights

Recognised as the "Best Academic Programme of the Year" at the FinTech Awards Wales, our course offers a unique opportunity to excel in the dynamic field of data science.

Designed for aspiring data enthusiasts, recent graduates and professionals seeking to enhance their analytical skills whether you're from a STEM background or looking to pivot into data-driven roles, this programme equips you with the expertise needed to excel in the evolving field of data science.

Course Modules

Compulsory
Applied Statistics for Data Science 20 Credits
Data Mining and Statistical Forecasting 20 Credits
Principles of Computing 20 Credits
Applied Machine Learning and Deep Learning 20 Credits
Big Data Engineering and its Applications 20 Credits
Project Management and Research Methodology 20 Credits
MSc Research Project 60 Credits

Learning Structure

Teaching
  • You'll learn in blocks of eight weeks, spending between 12-16 hours each week on lectures, tutorials and practical sessions and around four hours per week on coursework, general reading and other preparation.
Assessment
  • There are no exams and you'll be assessed on a dissertation project that will allow you to develop and demonstrate data collection, analysis and development management techniques.

Entry Requirements

  • A four-year undergraduate degree in STEM or business discipline with CGPA 2.75 or 55% of marks from recognised institution.

English Language Requirements

IELTS  Overall 6.0

Listening

5.5

Reading

5.5

Writing

5.5

Speaking

5.5
Language Accepts: IELTS, TOEFL, Pearson PTE, LanguageCert
Applicants who do not meet required IELTS or equivalent for direct entry may still become eligible by enrolling in a Pre-sessional English Language course to achieve this level.
No IELTS? No problem!
Got TOEFL, PTE, Duolingo, LanguageCert or OIETC? Instantly check your IELTS equivalency and see if you qualify for your dream university!
Accepts Medium of Instruction (MOI) Certificate.

Documentary Evidence List

  • Academic transcripts (Bachelor degree)
  • Degree certificate
  • English test (IELTS/ TOEFL/ PTE/ Duolingo - UKVI accepted)
  • Statement of Purpose (SOP)
  • 2 Recommendation Letters (LORs)
  • Updated CV/ Resume
  • Research Proposal (for Research/ PhD)
  • Work experience certificate(s) (if study gap)
  • Passport copy

Study Gaps

For applicants with an academic or professional gap of up to 5 years, admission is generally considered acceptable. If the gap exceeds this period, applications may still be successful but will typically be assessed on a case-by-case basis.

To strengthen your profile, it is important to:

  • Provide a clear explanation of how you spent the gap period (e.g., employment, further learning, personal responsibilities).
  • Emphasize the skills and experiences you developed during this time that are relevant to the program.
  • Demonstrate that your academic qualifications continue to meet the course entry requirements.

Disclaimer: The information provided on this page is sourced from the official university website. Please note that universities may update their course details, fees, entry requirements and any other related information at any time without prior notice. We recommend verifying the latest updates directly with the university.

Last reviewed on 24 September 2025.

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