Data Science
Program Overview
Covers statistics, machine learning, data visualization, and big data technologies. Students complete hands-on projects analyzing real-world datasets to extract actionable insights.
Program Brochure
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Program Course Structure
| Data Science | |||||||
| Semester I | Semester II | ||||||
| Course Code | Course Title | MAS | PhD | Course Code | Course Title | MAS | PhD |
| DS-CR-501 |
Programming for Data Science |
2 | 2 | DS-CR-550 |
Data Engineering and Architecture |
2 | 2 |
| DS-CR-502 |
Data Analytics and Visualization |
3 | 3 | DS-CR-551 | Deep Learning | 3 | 3 |
| DS-CR-503 |
Machine Learning for Data Science |
3 | 3 |
DS-EL- 561~570 |
Elective I | 2 | 2 |
| DS-CR-504 |
Research Methods for Data Science |
1 | `1 |
DS-EL-561- 570 |
Elective II | 2 | 2 |
| GC-NC-550 |
Entrepreneurship, Scientific Communication and Leadership (4hr) |
0 | 0 | GC-CR-501 | Development Policy | 3 | 3 |
| AI-NC-553 |
Case Studies in Ethics and Fairness in AI (1hr) |
0 | 0 | ||||
| DS-TH-699 | Thesis | 4 | 4 | ||||
| Semester III | Semester IV | ||||||
| Course Code | Course Title | MAS | PhD | Course Code | Course Title | MAS | PhD |
| DS-TH-699 | Thesis | 13 | 13 | DS-TH-699 | Thesis | 13 | 13 |
| Semester V | Semester VI | ||||||
| Course Code | Course Title | MAS | PhD | Course Code | Course Title | MAS | PhD |
| OA-TH-699 | Thesis | - | 10 | DS-TH-699 | Thesis | - | 10 |
| Total credit for Thesis = 30 credit | |||||||
| Total credit for Master in Applied Sciences course= 51 credit (15 credit core course + 6 credit Technical elective + 30 credit Thesis) | |||||||
| Total credit for Thesis = 50 credit | |||||||
| Total credit for Ph.D in Applied Sciences course= 75 credit (17 credit core course + 8 credit Technical elective + 50 credit Thesis) | |||||||
Timeline
Master of Applied Science in Data Science
| Semester I | Semester II | Semester III | Semester IV |
|
4 Core Course 1 Non-Credit Course |
• 3 Core Course • 2 Technical Elective • 1 Non-Credit Course • Proposal submission to Advisory Committee and Thesis work initiation |
Thesis Progress Presentation |
Comprehensive Exam Thesis Defense |
Ph.D of Applied Science in Data Science
| Semester I | Semester II | Semester III | Semester IV | Semester V | Semester VI |
|
• 4 Core Course • 1 Non-Credit Course |
• 3 Core Course • 1 Non-Credit Course • 2 Technical Elective |
• 1 Technical Elective • Proposal submission to Advisory Committee and Thesis work initiation |
• 1 Technical Elective • Thesis Work Initiation and Thesis Progress Presentation |
• Thesis Work Initiation and Thesis Progress Presentation |
• Comprehensive Exam • Thesis Defense |
