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Master of Science (Data Science and Analytics)
Course overview
| Qualification | Master's Degree |
| Study mode | Full-time |
| Duration | 18 months |
| Intakes | March, July, November |
| Tuition (Local students) | $ 4,000 |
| Tuition (Foreign students) | $ 6,000 |
About
The Master of Science in Data Science and Analytics program provides graduates with essential knowledge in handling large and complex data sets across various disciplines. Core modules cover topics such as Data Mining, Data Analytical Programming, Machine Learning, Big Data Management, and Data Visualization. Graduates will be well-equipped to integrate specialized field requirements with Data Science and Analytics, enhancing and revolutionizing data processes within organizations.
Successful completion of the Master’s degree requires each candidate to publish a minimum of two research articles in Scopus indexed journals with affiliation to Lincoln University College.
Admissions
Intakes
Fees
Tuition
- $ 4,000
- Local students
- $ 6,000
- Foreign students
Estimated cost as reported by the Institution.
Application
- Data not available
- Local students
- $ 181
- Foreign students
Student Visa
- $ 544
- Foreign students
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.
Entry Requirements
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 6.0 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.
Curriculum
- - Principles and Practices of Data Science and Analytics
- - Applied Statistics
- - Data Analytical Programming
- - Machine Learning for Data Science
- - Data Visualization and Visual Analytics
- - Big Data Analytics
- - Research Methodology for Capstone Project
- - Business Intelligence and Decision Analytics (Elective for Business Analytics)
- - Social Media Analytics (Elective for Business Analytics)
- - Predictive Analytics and Business Forecasting (Elective for Business Analytics)
- - Deep Learning (Elective for Data Engineering)
- - Natural Language Processing (Elective for Data Engineering)
- - Cloud Infrastructure (Elective for Data Engineering)
- - Capstone Project