Duration - 3 Years (Full time)


  • The course has a stronger focus on fundamental concepts underpinning Data Science and the coverage of recent industry-changing developments in AI, big data analytics, machine learning, Python Programming, Natural Language Processing and Data Programming.
  • The inclusion of a more substantial computation, statistical, and big data element into the course requires students with a stronger mathematical background, which is ensured by differentiated criteria for admission.
  • The course combines the Sri Lankan computing market demand with the wider research and development approaches in data science to provide the necessary knowledge portfolio for the graduates, both within the Sri Lankan context and the wider international trends.
  • The course is taught by a combination of flying faculty from University of Plymouth and local lecturers, all with recognised research track record within their field, that seeking to embed research-informed teaching throughout the learning experience and helping to ensure state of the art knowledge, skills and practice. Students will have the exciting opportunity to engage with world-leading researchers in areas such as artificial intelligence, machine learning, neural networks and further advanced computing paradigms, provided through the continuous alignment of the programme to the current University of Plymouth curriculum.
  • NSBM has strong links with the Sri Lankan industry, having signed a Memorandum of Understanding (MoU) with 25 organizations who have either a IT focus or include a substantive IT element in their infrastructure or. In the preliminary phases, the group was consulted by the programme team to ensure the relevance of the curriculum to the market needs.
  • In line with the University of Plymouth values, NSBM promotes learning through practice and doing, and a prominent feature the two stages of the degree is a practice module that provides a holistic learning experience for students, drawing on the rest of their taught content from that stage (and earlier) and combining it to produce outputs of a professional standard.
  • The focus on fundamental and state of the art Data Science topics further provides options to engage into postgraduate studies in Data Science, Business Analytics or Machine Learning and Artificial Intelligence.


  • To give students with a wide variety of qualifications an opportunity to realise their potential.
  • To enrich the curriculum content and teaching quality through the professional and/or research expertise of staff and through links to external organisations.
  • To encourage and support students while they develop and apply subject-specific and generic skills that will facilitate life-long learning and continuing professional development.
  • To produce graduates who can make a significant contribution to their chosen profession.
  • To provide an understanding of common machine learning and AI algorithms, Statistical and computational models, and to apply these techniques to create high quality computer systems.
  • To produce graduates who are technical experts, but who also have an awareness of the business, social, legal and ethical contexts of IT.
  • To encourage exploration and enthusiasm for both the subject of computing and to encourage creativity.

Aims of the Program

  • Technical understanding of data science body of knowledge.
  • Familiarity with common DS themes and principles such as Computational and statistical thinking, mathematical foundations, Model building and assessment, Algorithms and software foundation, Data curation, Knowledge transference – communication and responsibility.
  • Appreciation of the interplay between theory and practice.
  • System-level perspective; ability to think at multiple levels of detail and abstraction.
  • Commitment to professional responsibility, recognizing the social, legal, ethical, and cultural issues inherent in the discipline of data science and computing.
  • Awareness of the broad applicability of data science, promoting dual coverage combining both data science fundamentals and applications, exploring why people turn to data to explain contextual phenomena.
  • Appreciation of domain-specific knowledge


Year 1

  • Introduction to Computer Science
  • Programming in C
  • Professional Development
  • Mathematics for Computing
  • Algorithms and Data Structures
  • Database Management Systems
  • Web Based Application Development
  • Object Oriented Programming with C#
  • System Analysis and Design
  • Computer Architecture

Year 2

  • Computational theory and statistics for computing
  • Information Management & Retrieval
  • Data Programming with R
  • Computing Group Project
  • Statistics for Data Science
  • Data Science in Python

Year 3

  • Computing Project
  • Natural Language Processing
  • HCI, computer graphics, and visualization
  • AI and Machine Learning
  • Big Data Analytics


Three Passes in Physical Science and Biological Science streams in a single sitting, at one of the following examinations or equivalent foreign qualifications is the minimum entry requirement.

  • G.C.E. Advanced Level examination conducted by the Department of Examinations, Sri Lanka.
  • G.C.E Advanced Level examination conducted by Pearson Edexcel, UK (London A/L).
  • International Advanced Level examination conducted by Pearson Edexel, UK.
  • G.S.E Advanced Level examination conducted by Cambridge International Examination, UK

“Non-STEM background students are required to undergo a selection test to qualify for the enrollment in the Plymouth BSc.(Hons) Data Science Program, ensuring readiness for the Plymouth program registration.”

  • Year 1 - 1,200,000 LKR
  • Year 2 - 700,000 LKR
  • Year 3 - 700,000 LKR
  • Registration Fee - 10,000 LKR
  • Library Fee - 5,000 LKR
Four Years (Full Time)
2,600,000 LKR
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Semester-based Flexible Course Fee Structure, Contact us for more details     +94 11 544 5000

Student Loan facilities are available from 

Send us an inquiry to ask about payment plans and loan facilities


  • Data Scientist
  • Machine Learning Engineers
  • BI Engineers
  • Consultants
  • Web Analytics Engineers
  • Software Engineers
  • Deployment Engineers
  • Computer Scientists
  • Research Engineers
  • Research Scholars
  • Robotic Engineer