The Faculty of Information Science and Technology in Universiti Kebangsaan Malaysia offers various computing programmes. However, the Master of Data Science is uniquely designed for special individuals and their organization’s needs.We collaborate with the Malaysia Administrative Modernisation and Management Planning Unit (MAMPU) and team with ABYRES Sdn.Bhd, to ensure best knowledge delivery
| No. | Course Learning Outcome |
|---|---|
| 1. | Analyze and evaluate data in depth. |
| 2. | Support the development and deployment of innovative big data platforms for advanced analytics. |
| 3. | Solve problems with innovative solutions for business purposes. |
| 4. | Understand data and information modelling to design, construct and evaluate databases and data warehouses for structured and unstructured data. |
| 5. | Apply data analysis methods and techniques for changing raw data into valuable and useful information. |
A Bachelor’s Degree in computing from the National University of Malaysia or any other higher education institution approved by the Senate with a minimum Cumulative Grade Point Average (CGPA) of 2.75;
OR
A Bachelor’s Degree in computing from the National University of Malaysia or any other higher education institution approved by the Senate with a CGPA of a minimum 2.50 but not reaching 2.75, can be considered subject to internal assessment;
OR
A Bachelor’s Degree in computing from the National University of Malaysia or any other higher education institution approved by the Senate with a CGPA below 2.50 with at least 5 years of working experience in the field of computing can be considered;
OR
A Bachelor’s Degree in a different field from the National University of Malaysia or any other higher education institution approved by the Senate with a minimum CGPA of 2.75, AND have no less than 5 years of working experience in the field of computing,
AND need to complete prerequisite courses set by the program;
OR
Other qualifications were equivalent to a Bachelor’s Degree and have other qualifications or experience approved by the Senate.
Minimum 550 (PBT) / 46-59 (iBT) score for the Test of English as a Foreign Language (TOEFL)
OR
5.5 for the International English Language Testing System (IELTS)
OR
Band 3 for the Malaysian University English Test (MUET)
OR
level B2 for the Common European Framework of Reference for Languages (CEFR/CEFRL)
| Structure | Course Credit | Course |
|---|---|---|
| Compulsory | 20 credits (equivalent to 5 courses) |
TC6424 Fundamental of Data Science |
| TR6124 Statistical Methods for Data Analytics | ||
| TC6444 Machine Learning for Data Science | ||
| TU6314 Business Analytics | ||
| TM6114 Research Method in Computing | ||
| Electives | 8 credits (equivalent to 2 courses) | TU6434 Big Analytics & Management |
| TP6234 Unstructured Data Analyticvs | ||
| Project | 8 credits | TT6074 Project 1 (4 credits) |
| TT6078 Project II (8 credits) | ||
| Total | 40 credits | |
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