Master of Science (Data Science and Analytics) programme will equip graduates with the core Data Science and Analytics knowledge required to work with large and complex data sets in multidisciplinary fields. The core modules of the programme include Data Mining, Data Analytical Programming, Machine Learning for Data Science, Big Data Storage and Management and Data Visualisation and Visual Analytics. Graduates will have strong capabilities to integrate the specialised filed requirements with Data Science and Analytics to improve and transform the Data Science process within an organisation.
For successful completion of Master’s degree each candidate should publish minimum of two research articles in Scopus indexed journals with Lincoln University College affiliation.
The programme Master of Science (Data Science and Analytics) will produce professionals who can be able to:
- Produce knowledgeable and be technically competent in the field of Data Science and Analytics in line with industry requirement locally and globally.
- Perform well as a team player, demonstrate good leadership qualities in an organization, and be effective in communication.
- Solve problems related to the field of IT creatively, innovatively, ethically, using numerical and technical skills, and through sustainable approach to solve Data Science and Analytics related problems.
- Demonstrate entrepreneurship skills and recognize the need of lifelong learning, as well using a broad range of information, media, and technology applications for successful career advancement.
The Master of Science (Data Science and Analytics) programme blends scientific knowledge with practical learning to prepare you to further your career in today’s data-driven environment. Their program-acquired abilities will prepare them for graduate-level positions in this industry. The most prominent positions held by someone having this degree are listed in below:
- Data Scientist
- Big Data Analyst
- Machine Learning Engineer
- Mining Analyst
- Data Modeler
- Data Architect/Engineer
- Qualitative Analyst
| Sl.No. | MQA Subject Code | Subject Name | Credits |
|---|---|---|---|
| 1. | MDSA 7013 | Principles and Practices of Data Science and Analytics | 4 |
| 2. | MDSA 7023 | Applied Statistics | 4 |
| 3. | MDSA 7033 | Data Analytical Programming | 4 |
| 4. | MDSA 7043 | Machine Learning for Data Science | 4 |
| 5 | MDSA 7053 | Data Visualization and Visual Analytics | 4 |
| 6. | MDSA 7063 | Big Data Analytics | 4 |
| 7. | MDSA 7073 | Research Methodology for Capstone Project | 4 |
| Elective Groups (Students need to choose any one group of 3 modules) for specializations on Business Analytics / Data Engineering | |||
| Elective Group: Business Analytics | |||
| 8. | MDSA 7083 | Business Intelligence and Decision Analytics | 3 |
| 9. | MDSA 7093 | Social Media Analytics | 3 |
| 10. | MDSA 7103 | Predictive Analytics and Business Forecasting | 3 |
| Elective Group: Data Engineering | |||
| 11. | MDSA 7113 | Deep Learning | 3 |
| 12. | MDSA 7123 | Natural Language Processing | 3 |
| 13. | MDSA 7133 | Cloud Infrastructure | 3 |
| 14. | MDSA 71412 | Capstone Project | 12 |
i. A Bachelor’s Degree in Computing or related fields with a minimum CGPA of 2.75 or equivalent, as accepted by the Lincoln University College Senate; or
ii. A Bachelor’s Degree in Computing or related fields or 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
iii. A Bachelor’s Degree in Computing or related fields or equivalent, with CGPA less than 2.50, with a minimum of 5 years working experience in a relevant field may be accepted; or
iv. Other equivalent qualifications recognized by the Malaysian Government.
For candidates without Computing Degree, prerequisite modules in computing must offered to adequately prepare them for their advanced study.
English Requirements :
International students must have proof of good proficiency in verbal and written English. For example, International English Language Testing System (IELTS) score of 5.5 or its equivalent. If a student does not meet this requirement, HEPS must offer English proficiency courses to ensure that the student’s proficiency is sufficient to meet the needs of the programme.