What is your next education pathway?

The BSc (Hons) Data Science degree, awarded by Coventry University will provide students with essential training in probability, statistics, mathematics and computational concepts and techniques for the visualisation, modelling and analysis of large datasets. This skills-rich degree will provide students with the necessary training for employment in numerous fields as a data scientist, analyst, or similar, requiring a critical and independent mind as well as problem solving.

Ninety percent of the data in the world today has been created in the last two years alone, rendering traditional data processing applications inadequate and increasing the demand for sophisticated data analysts who can collate, interpret and draw value from complex data sets.

Businesses and organisations from almost every sector have woken up to the power of data analytics. Used effectively, they can inform decision making within business and finance, predict and dispense medical treatment within the healthcare system and help improve performance in sports or interpret data from smartphone apps.

Upon completion of this degree, you will receive a qualification awarded by Coventry University. 

Department
Department
BUSINESS ANALYTICS CENTER
Campus
Campus
Kirulapone NIC
Level
Level
Degree Programmes
Method
Method
Part Time
Duration
Duration
3 Years
Medium
Medium
English

Entry Requirements

Year 01: Advanced Diploma in Data Science

  • G.C.E. A/L qualification with 3 Simple Passes (i.e. 3 S Passes) from the Physical / Bio Science stream OR Technology Stream.

Year 02: Higher National Diploma in Data Science

  • Those who have completed the Advanced Diploma in Data Science from the NIBM
     

  • Lateral entry points: Those who have completed the Advanced Diploma in a discipline with significant IT, Computing, Mathematics and Statistics content in a recognized institution (upon review by the Data Science academic panel of NIBM) are eligible to enroll for the 2nd year of the degree. 

Year 03: BSc (Hons) in Data Science

  • Successful completion of Higher National Diploma in Data Science from NIBM 

  • Lateral entry points: Those who have completed the Higher National Diploma in a discipline with significant IT, Computing, Mathematics and Statistics content in a recognized institution (eligibility will be reviewed by Coventry University) with 2.5 years’ experience in the relevant field are eligible to enroll for the final year of the degree. 

Commencement

  • NIC (Kirulapone) - 12th March 2025 (Year 01)

Programme Fees

Current Fee Structure

Year 01 - Course Fee: LKR 300,000/= + Registration Fee: LKR 5,000/=

Year 02 - Course Fee: LKR 400,000/=  + Registration Fee: LKR 5,000/=

Year 03 - Course Fee: LKR 1,000,000/= + Registration Fee: LKR 8,000/=

*Subject to change without prior notice. Conditions apply.

Awarding University

Course Structure and Modules

Year 01: Advanced Diploma in Data Science

  • Introduction to Programming in Python and R

  • Calculus for Data Science

  • Linear Algebra for Data Science

  • Statistics 1 for Data Science and Business Analytics

  • Cloud Computing

  • Data Science for Business and Digital Marketing

  • Data Structures and Algorithms 

  • Data Wrangling

  • Statistics 2 for Data Science and Business Analytics

  • SQL Databases for Data Science and Business Analytics 

  • Use of NoSQL Databases for Data Science 

  • Storytelling with Data

  • Case Study in Data Science


Year 02: Higher National Diploma in Data Science

  • Data Visualization

  • Interactive Dashboards using Python

  • Machine Learning 01

  • Time Series Analysis for Data Science

  • Information Retrieval and Analytics

  • Data Engineering

  • Financial Analytics

  • Machine Learning 02

  • Big Data Analytics

  • Deep Learning 

  • Operations Research

  • Data Science Research Project

  • Industrial Training


Year 03: BSc (Hons) in Data Science

  • Cryptography and Information Theory 

  • Machine Learning and Related Applications 

  • Advanced Topics in Statistics 

  • Professional and Academic Skills  

  • Optimization 

  • Final Year Project