fbpx

* All information is provided by CQA.
* All information is correct at the time of publication. UniKL reserves the right to make changes to the programmes offered and its content without prior notice. Programmes will be offered subject to MQA approval.

Master in Data Science

Sarjana dalam Sains Data

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



Programme Educational Objectives (PEOs)

  • 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;
  • PEO03 : 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.


Programme Learning Outcomes (PLOs)

  • PLO1 : 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 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 : Practise good teamwork as members or a leader in a group;
  • PLO6 : Demonstrates knowledge of business practice and echnopreneurial competencies in data science;
  • PLO7 : Displays behaviour that is consistent with codes of professional ethics and responsibility.
Career Path :

  • Data Scientist
  • Data Analyst
  • System Analyst
  • Data Architecture
  • Big Data Engineer
  • Artificial Intelligence Analytics Scientist
  • Big Data Solution Architect
  • Business Intelligence Analyst
Semester 1 (Year 1)
  • Data architecture and advanced databases
  • Probability and statistics for data science
  • Data mining
  • Acquisition and visualisation analytics
  • Innovation Technology & Entrepreneurship


Semester 2 (Year 1)
  • Big data architecture
  • Advanced Machine learning
  • ** Elective Courses
  • Research methodology


Semester 3 (Year 2)
  • Research project


Elective
  • ** Natural language processing
  • ** Information systems and Business Intelligence
  • ** Information / Data security
Fees:
Local Student :

  • Full Fee (Full Time-Local): RM42,500
  • Full Fee (Part Time-Local): RM42,900

International Student :

  • Full Fee (Full Time-International): RM58,700

Entry Requirement:

  • A Bachelor’s Degree of computing or a relevant field or its equivalent, with a minimum CGPA of 2. 75; OR
  • A Bachelor’s Degree of computing or a relevant field 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 and working experience in a relevant field; OR
  • A Bachelor’s Degree of computing or related in computing or its equivalent, with CGPA less than 2.50, with a minimum of 5 years working experience in a relevant field may be accepted.
  • Passed the English language proficiency either with minimum IELTS Band 5.5 or TOEFL 525 (International students)

 

Quick Points

Campus:
UniKL MIIT

Programme Status:
Provisional Accredited

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

Specialisation:
Computing (Computer Science)

Study Mode:
Full-time
Part Time

Study Level:
Master (Coursework)

Intake:
January & July

Duration:
Full Time : 1.5 – 3 Years
Part Time : 2 – 5 Years

CENTRE OF PREPARATORY STUDIES
Universiti Kuala Lumpur
Level 26, 1016, Jalan Sultan Ismail,
50250 Kuala Lumpur

Tel:  +603 - 2175 4162
Fax: +603 - 2175 4440
Email: cps@unikl.edu.my

UNIVERSITI KUALA LUMPUR

1016, Jalan Sultan Ismail,
50250 Kuala Lumpur

+603 - 2175 4000

+603 - 2175 4001

CONNECT WITH #UniKL

MOE Registration Certification No: DU011(W)

UniKL website developed & managed by
Corporate Branding & Strategic Communication
Department (CBSCD)

UniKL