Master in Data Science

DURATION:
1.5 - 2 years

 PROGRAMME CODE

JPT/BPP (N/481/7/0814) 11/24, MQA/PSA 12981

NEC: 481

 

PROGRAMME SUMMARY

 

PROGRAMME DETAILS
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


CAREER OPPORTUNITIES FOR STUDENTS

  • Data Scientist
  • Data Analyst
  • System Analyst
  • Data Architecture
  • Big Data Engineer
  • Artificial Intelligence Analytics Scientist
  • Big Data Solution Architect
  • Business Intelligence Analyst

 

PROGRAMME DETAILS

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.

 

ENTRY REQUIREMENTS

  • 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)
1 Highly knowledgeable, strong technical competent and innovative solution in Data science;
2 Effective leaders with teamwork skills, as well as verbal and non-verbal interpersonal communication skills;
3 Committed towards the importance of lifelong learning and continuous improvement;
4 Professional, ethical, and socially responsible; and
5 Capable of embarking on business and technopreneurial activities.
NO Program Learning Outcomes (PLO)
1 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;
2 Evaluate and analyse data science solutions in terms of their usability, efficiency and effectiveness;
3 Develop data science solutions and use necessary tools to analyse their performance;
4 Apply existing techniques of research and enquiry to acquire, interpret and extend, knowledge in data science;
5  Communicate and function effectively in a group;
6 Discuss awareness and understanding of business practice and technopreneurial competencies in data science;
7 Demonstrate behaviour that is consistent with codes of professional ethics and responsibility.

 

MODULES

SEMESTER SUBJECTS
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
Elective
  • ** Natural Language Processing
  • ** Information Systems and Business Intelligence
  • ** Information / Data Security

TOTAL CREDIT TO GRADUATE:40

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