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Master of Data Science

Duration:180 credit hours
Intake: February


Learn how to make decisions using measurable data-driven insights.

The ability to turn data into information, knowledge and innovative products is a skill in high demand within industry. By completing a strong core of Computer Science and Statistics courses, you will gain a unique combination of skills in Data Science and be able to comprehend, process and manage data effectively to extract value from it. Graduates will be critical, reflective practitioners able to pursue professional goals and further postgraduate study.

We also offer the Master of Data Science (MDataSci) as a 240-point taught masters as a March intake only. This is suitable for students who have a background in either Computer Science or Statistics, but not both. Students who have majored in Data Science, or a combination of computer science and Statistics, should apply for the 180-point taught masters.

Programme structure

60 points:

  • COMPSCI 752 Big Data Management
  • COMPSCI 760 Datamining and Machine Learning
  • STATS 763 Advanced Regression Methodology
  • STATS 769 Advanced Data Science Practice

At least 15 points from:

  • STATS 705 Topics in Official Statistics
  • STATS 730 Statistical Inference
  • STATS 783 Simulation and Monte Carlo Methods
  • STATS 784 Statistical Data Mining
  • STATS 787 Topics in Statistical Computing

At least 15 points:

  • COMPSCI 711 Parallel and Distributed Computing
  • COMPSCI 720 Advanced Design and Analysis of Algorithms
  • COMPSCI 734 Web, Mobile and Enterprise Computing
  • COMPSCI 750 Computational Complexity
  • COMPSCI 753 Uncertainty in Data

Up to 45 points from:

  • COMPSCI 705 Advanced Topics in Human Computer Interaction
  • COMPSCI 715 Advanced Computer Graphics
  • COMPSCI 732 Software Tools and Techniques
  • COMPSCI 761 Advanced Topics in Artificial Intelligence
  • COMPSCI 765 Interactive Cognitive Systems
  • COMPSCI 767 Intelligent Software Agents
  • ENGSCI 711 Advanced Mathematical Modelling
  • ENGSCI 755 Decision Making in Engineering
  • ENGSCI 760 Algorithms for Optimisation
  • ENGSCI 761 Integer and Multi-objective Optimisation
  • ENGSCI 762 Scheduling and Optimisation in Decision Making
  • ENGSCI 763 Advanced Simulation and Stochastic Optimisation
  • ENGSCI 768 Advanced Operations Research and Analytics
  • HLTHINFO 723 Health Knowledge Management
  • HLTHINFO 728 Principles of Health Informatics
  • HLTHINFO 730 Healthcare Decision Support Systems
  • INFOSYS 700 Digital Innovation
  • INFOSYS 720 Information Systems Research
  • INFOSYS 722 Data Mining and Big Data
  • INFOSYS 737 Adaptive Enterprise Systems
  • INFOSYS 740 System Dynamics and Complex Modelling
  • MATHS 715 Graph Theory and Combinatorics
  • MATHS 761 Dynamical Systems
  • MATHS 765 Mathematical Modelling
  • MATHS 766 Inverse Problems
  • MATHS 769 Stochastic Differential and Difference Equations
  • MATHS 770 Advanced Numerical Analysis
  • OPSMGT 752 Research Methods – Modelling
  • OPSMGT 757 Project Management
  • OPSMGT 760 Advanced Operations Systems
  • OPSMGT 766 Fundamentals of Supply Chain Coordination
  • SCIENT 701 Accounting and Finance for Scientists
  • SCIENT 702 Marketing for Scientific and Technical Personnel
  • SCIENT 705 Research Commercialisation
  • STATS 701 Advanced SAS Programming
  • STATS 710 Probability Theory
  • STATS 726 Time Series
  • STATS 731 Bayesian Inference
  • STATS 770 Introduction to Medical Statistics
  • STATS 779 Professional Skills for Statisticians
  • STATS 780 Statistical Consulting
  • Other 700-level courses approved by the programme director

45 points:

DATASCI 792, 792a, 792b Dissertation

Entry criteria

Taught 180/240 points

You must have completed an undergraduate science degree at a recognised university (or similar institution) in a relevant discipline with a Grade Point Equivalent of 4.5.

Relevant disciplines include data science, or a mixture of computer science and statistics. A minimum amount of study in a relevant discipline is required – this would be at least a major, field of study, or approximately 30 percent of your degree, including a mix of introductory and advanced courses.

IELTS (Academic): Overall score of 6.5 and no bands less than 6.0; Internet-based TOEFL (iBT): Overall score of 90 and written score of 21; Paper-based TOEFL: Overall score of 68 and a writing score of 21; Cambridge English: Advanced (CAE) or Cambridge English Proficiency (CPE): Overall score of 176 and no bands below 169; Pearson Test of English (PTE) Academic: Overall score of 58 and no PTE Communicative score below 50; Foundation Certificate in English for Academic Purposes (FCertEAP): Grade of B-; Michigan English Language Assessment Battery (MELAB): 85.

180 credit hours

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INDIAKochi Office
Cliftons Study Abroad
2nd Floor, Kudiyirickal Towers
Metro Pillar No 528, Palarivattom
Kochi, Kerala - 682025
UKLondon Office
71-75 Shelton Street,
Covent Garden,
London, United Kingdom,
OUR LOCATIONSWhere to find us
GET IN TOUCH Social Links
Like and follow us on our Social links to know us better

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