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MSc In Digital Technology And Analytics
About
The MSc in Digital Technology and Analytics is designed to equip students with advanced knowledge and practical skills at the intersection of digital technology and data analytics. This programme offers a unique opportunity to stay ahead in one of the world's fastest-evolving fields by integrating cutting-edge technologies with analytical strategies.
Students will gain in-depth expertise in emerging digital technologies, including Cloud Computing, Internet of Things (IoT), Data Analytics, and Machine Learning. This comprehensive curriculum blends technical knowledge with analytical tools, preparing graduates to leverage technology for data-driven decision-making and innovation. The programme is ideal for individuals aiming to develop a competitive edge in the digital economy, equipping them with the skills to drive technological transformation across industries.
Key facts
| Qualification | Master's Degree |
| Qualification Subtype | Master of Science (MSc) |
| Coursework / Research | Coursework |
| Study mode | Full-time |
| Duration | 1 year |
| Intakes | January, June, October |
| Tuition (Local students) | $ 10,258 |
| Tuition (Foreign students) | $ 14,006 |
Subjects
-
Information Tech (IT)
Duration
1 year
Tuition fees
| Description | Local students | Foreign students |
|---|---|---|
| Tuition fee | $ 10,258 | $ 14,006 |
| Miscellaneous fees | Data not available | Data not available |
| Total estimated cost of attendance | $ 10,258 | $ 14,006 |
| Estimated cost per year | $ 10,258 | $ 14,006 |
Estimated cost as reported by the institution. There may be additional administrative fees. Please contact for the latest information.
Every effort has been made to ensure that information contained in this website is correct. Changes to any aspects of the programmes may be made from time to time due to unforeseeable circumstances beyond our control and the Institution and EasyUni reserve the right to make amendments to any information contained in this website without prior notice. The Institution and EasyUni accept no liability for any loss or damage arising from any use or misuse of or reliance on any information contained in this website.
Admissions
Intakes
Entry Requirements
- A Bachelor’s degree in Computing or related fields with a minimum CGPA of 2.50, as accepted by the HEP Senate; OR
- A Bachelor’s degree in Computing or related fields or equivalent with a minimum CGPA of 2.00 can be accepted subject to a minimum of FIVE (5) years of working experience in the related fields and rigorous internal assessment; OR
- Other qualifications equivalent to a Bachelor’s degree in the field of Computing or related fields recognised by the Government of Malaysia must undergo appropriate bridging courses as determined by the HEP;
- Candidates without a qualification in the related fields or relevant working experience must undergo appropriate bridging courses as determined by the HEP and meet a minimum CGPA of 2.00 with minimum of FIVE (5) years of working experience in the related fields, and rigorous internal assessment.
English Language Requirements
Local and International Students
- IELTS: Band 6.0
International applicants who do not meet the English Language requirements will need to improve their proficiency by enrolling on the English for Tertiary Education programme (R/KJP/00920-00929) which helps them prepare for attaining a required band score. Placement into the various levels of the English for Tertiary Education programme depends on the English Language qualification students have at the point of admission and/or the outcome of the English Placement Test.
Curriculum
- Internet of Everything(IoE) MDT1001
- Machine learning MDT1002
- Python programming for Data analysis MDT1003
- Research Techniques In Computer Science/ Research methods MIC1003/MDT1004
- AI & Deep Learning MDT1005
- Data science MDT1006
- Project (Dissertation) MDT 1011
Electives (choose any 2)
- Big Data Analytics MDT1007
- Digital innovation (AR/VR) MDT1008
- Web technology and Cloud computing MDT1009
- Data visualization MDT1010