Master in Data Science

2 years
JPT/BPP (N/481/7/0814) 11/24, MQA/PSA 12981
NEC: 481  
Institute Institute of Postgraduate Studies (IPS, UniKL City Campus)
Specialization Data Science
Intake January, April, July, October
Duration Full Time: 1.5 years Part-time: 2 years
Category Master by Coursework
  • Data Scientist
  • Data Analyst
  • System Analyst
  • Data Architecture
  • Big Data Engineer
  • Artificial Intelligence Analytics Scientist
  • Big Data Solution Architect
  • Business Intelligence Analyst
This programme will be the first dual Master degree in Data Science in Malaysia. At the end of the program, the candidates will receive two certifications from both Universiti Kuala Lumpur (UniKL) and La Rochelle Université (LRU), France. All taught courses will be conducted as a modular basis at UniKL MIIT by joint academicians between UniKL and LRU. This Master programme is a valuable addition to the existing curriculum and relates to various and technical analytical specialisations offered by UniKL and LRU.
  • Bachelor’s Degree or its equivalent, with a minimum CGPA of 2.75;
  • OR
  • Bachelor’s Degree or its equivalent, with a minimum CGPA of 2.50 and not meeting CGPA of 2.75, can be accepted subject to rigorous internal assessment process;
  • OR
  • Bachelor’s Degree or its equivalent, with CGPA less than 2.50, with a minimum of 5 years working experience in a relevant field may be accepted.
  • For candidates without Computing Degree, prerequisite modules in computing must be offered to adequately prepare them for their advanced study.
NO Programme Educational Outcomes (PEO)
PEO1 Highly knowledgeable, strong technical competent and innovative solution in Data science;
PEO2 Effective leaders with teamwork skills, as well as verbal and non-verbal interpersonal communication skills;
PEO3 Committed towards the importance of lifelong learning and continuous improvement;
PEO4 Professional, ethical, and socially responsible; and
PEO5 Capable of embarking on business and technopreneurial activities.
NO Program Learning Outcomes (PLO)
PLO1 Apply and integrate knowledge concerning current research issues in Data science and produce work that is at the forefront of developments in the domain of the Data science;
PLO2 Evaluate and analyse data science solutions in terms of their usability, efficiency and effectiveness;
PLO3 Develop data science solutions and use necessary tools to analyse their performance;
PLO4 Apply existing techniques of research and enquiry to acquire, interpret and extend, knowledge in data science;
PLO5  Communicate and function effectively in a group;
PLO6 Discuss awareness and understanding of business practice and technopreneurial competencies in data science;
PLO7 Demonstrate behavior that is consistent with codes of professional ethics and responsibility.
Semester 1
  • Data Architecture and Advanced Databases
  • Probability and Statistics for Data Science
  • Data Mining
  • Acquisition and Visualisation Analytics
  • Innovation Technology & Entrepreneurship
Semester 2
  • Big Data Architecture
  • Advanced Machine learning
  • Research Methodology
Semester 3
  • Research Project
Semester 4
  • ** Natural Language Processing
  • ** Information Systems and Business Intelligence
  • ** Information / Data Security


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