The Master of Science in Data Science and Artificial Intelligence (M.Sc. DSAI) is a dynamic, two-year postgraduate program designed to equip students with the essential knowledge and skills for a successful career in the rapidly evolving fields of Data Science (DS) and Artificial Intelligence (AI). This program blends core courses in DS and AI providing a comprehensive understanding and integration of these two critical domains. Students gain the ability to analyze complex datasets, develop AI models, and implement innovative solutions to address real-world challenges across diverse industries, fostering their ability to make data-driven decisions and drive impactful change.
Key features of the program include an interdisciplinary core curriculum, specialization tracks, practical application and theory, professional development, and preparation for the future. Upon completion, graduates possess a unique combination of skills, ready to address the challenges of DS and AI in various roles across industries. This program is not just a pathway to a career; it is a gateway to becoming a leader in a field that drives innovation, shapes the future of technological advancement, and in indispensable for addressing the data-driven challenges of today’s interconnected world.
Program Duration:
Two years
Admission Requirements:
1. Bachelor degree in Data Science and/or Artificial Intelligence from an accredited higher education institution with a minimum GPA of 3.0 on a 4.0 scale. In addition, bridging courses may be required;
OR
2. Bachelor degree in a related discipline, such as Computer Science, Information Systems, IT, Software Engineering, Electronic Engineering, Bioinformatics, Mathematics, Statistics, or any other field with a strong quantitative, computational, or engineering orientation, from an accredited higher education institution with a minimum GPA of 3.0 on a 4.0 scale. In addition, bridging courses may be required.
1. The required score on the University English Placement Test or a passing score from another approved internationally recognized English language test, as validated by the Admissions & Registration Directorate; OR
2. A valid (within two years) IELTS Academic Test Report Form with an overall band score of 6.0, with no individual band score (reading, writing, speaking, and listening) below 6.0; OR
3. A valid (within two years) TOEFL iBT score of 72 and minimum scores of 17 in listening, 18 in reading, 20 in speaking, and 17 in writing.
Applicants are expected to have a proficient understanding of calculus, linear algebra, probability, and statistics at the undergraduate level.
1. Academic transcripts related to the Bachelor degree and/or post graduate diploma presented upon application;
AND
2. A satisfactory performance in the personal interview with the Admissions Committee.
Study Plan:
| COURSE NUMBER |
COURSE TITLE | requisite | HOURS/WEEK | |||
|---|---|---|---|---|---|---|
| PRE-req | CO-req | CR | LEC | LAB | ||
| SEMESTER 1 | ||||||
| DSAI5101 | Principles of Data Science & Machine Learning | - | - | 3 | 2 | 3 |
| AICC5102 | Principles of AI | - | - | 3 | 2 |
3 |
| DSAI5102 | Data Architecture & Engineering | - | - | 3 | 2 | 3 |
| Semester 1 Total: | 9 | 6 | 9 | |||
| SEMESTER 2 | ||||||
| DSAI5201 | Data governance & Responsible AI | DSAI5101 | - | 3 | 2 | 2 |
| DSAI5202 | Advanced Deep Learning | - | - | 3 | 2 | 3 |
| AICC5204 | Research Methods & Professional Development |
- |
- | 3 | 3 | 0 |
| Semester 2 Total: | 9 | 7 | 5 | |||
| Year 1 Total: | 18 | 13 | 14 | |||
| COURSE NUMBER |
COURSE TITLE | requisite | HOURS/WEEK | |||
|---|---|---|---|---|---|---|
| PRE-req | CO-req | CR | LEC | LAB | ||
| SEMESTER 3 | ||||||
| DSAI6101 | Advanced Natural Language Processing | DSAI5101 | - | 3 | 2 | 3 |
| AICC6103 | Computing Seminar | AICC5204 | - | 1 | 1 | 0 |
| Elective - Select 1 of 3 | ||||||
| DSAI6102 | Advanced Computer Vision | DSAI5202 | - | 3 | 2 | 3 |
| DSAI6103 | Advanced Reinforcement Learning | DSAI5101 | - | 3 | 2 | 3 |
| AICC6102 | AI Systems Engineering | AICC5202 OR DSAI5102 | - | 3 | 2 | 3 |
| Research or Professional Track- Select 1 of 2 | ||||||
| AICC6104 | Computing Research Thesis Project 1 | AICC5204 | - | 3 | 0 | 9 |
| AICC6110 | Selected Topics for Computing Graduation Project | AICC5202 OR DSAI5101 | - | 3 | 3 | 0 |
| Semester 3 Research Track Total: | 10 | 5 | 15 | |||
| Semester 3 Professional Track Total: | 10 | 8 | 6 | |||
| SEMESTER 4 | ||||||
| Research or Professional Track: Select 1 of 2 | ||||||
| AICC6204 | Computing Research Thesis Project II | AICC5204 & AICC6104 | - | 3 | 0 | 9 |
| AICC6210 | Computing Graduation Project | AICC5204 & AICC6110 | - | 3 | 0 | 9 |
| Elective - Select 1 of 3 | ||||||
| DSAI6201 | Business Intelligence & Data Analytics | DSAI5101 | - | 3 | 2 | 3 |
| DSAI6202 | Software Engineering for Machine Learning Systems | DSAI5101 | - | 3 | 2 | 3 |
| DSAI6203 | AI in Healthcare | DSAI5101 | - | 3 | 2 | 2 |
| DSAI6205 | Generative AI & LLMs | DSAI5102 | - | 3 | 2 | 3 |
| Semester 4 Research Track Total: | 6 | 2 | 12 | |||
| Semester 4 Professional Track Total: | 6 | 2 | 12 | |||
| Year 2 Research Track Total: | 16 | 7 | 27 | |||
| Year 2 Professional Track Total: | 16 | 10 | 18 | |||
| M.Sc. DSAI Program Total (Research Track): | 34 | 20 | 41 | |||
| M.Sc. DSAI Program Total (Professional Track): | 34 | 23 | 32 | |||
Graduate Future Pathways:
Graduates of the Master of Science in Data Science and Artificial Intelligence (M.Sc. DSAI) program may choose to engage in advanced research and development, policy and regulation, entrepreneurship and startups, corporate leadership and strategy, educational and academic contributions, industry-specific applications, international development and data-driven innovation, technology consulting, public sector and governmental roles, and ethics and responsible AI.
Career Opportunities:
The Master of Science in Data Science and Artificial Intelligence (M.Sc. DSAI) program is an applied degree with learning outcomes closely linked to the labor market. A wide range of career opportunities in the field currently exist and include, but are not limited to, the following:
-
Senior Data Science Strategist
-
AI & Machine Learning Engineer
-
Big Data Analytics Expert
-
Data Architecture & Infrastructure Specialist
-
Operations Research & Optimization Analyst
-
Actuarial & Risk Management Analyst
-
Computational Research Scientist in AI
-
Ethical AI Policy & Governance Advisor
-
Market Insights & Survey Analytics Expert
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Data-Driven Innovation Consultant