Artificial Intelligence
Program Overview
Artificial intelligence has become an important part of our society. It has created opportunities to transform existing structures and models in businesses, the public sector, and society. Machine learning, an important component for building AI applications, is gaining popularity in automated decision-making with the availability of large-scale data and affordable infrastructure. With these developments, skilled AI and ML engineers and data scientists are in high demand with a wide range of career opportunities everywhere. The program aims to give fundamental knowledge and practical skills needed to design, build, and apply AI systems in a chosen area of specialization. Designing application that delivers an impact and contributes to sustainable development is an important aspect of the training. Students will undertake projects relevant to one or more Sustainable Development Goals (SDGs). Furthermore, these goals are introduced in the elective courses along with the use cases in core courses where AI has had an impact. This graduate program has been developed to fill the gap in the availability of skilled AI scientists and engineers in Nepal. The program will offer rigorous training in the foundations and application-oriented artificial intelligence. Graduates of this program will have explored a variety of domains such as agriculture, healthcare, industry automation and social media to contribute to economies and societies. They will be capable of undertaking careers in the industry as well as academia.
Program Course Structure
| Artificial Intelligence | |||||||
| Semester I | Semester II | ||||||
| Course Code | Course Title | MAS | PhD | Course Code | Course Title | MAS | PhD |
| AI-CR-501 | Machine learning | 3 | 3 | AI-CR-550 | Computer Vision | 3 | 3 |
| AI-CR-502 | Practical Data Science with Python |
2 | 2 | AI-CR-551 | Natural Language Processing |
3 | 3 |
| AI-CR-503 | Group project in people-centred AI |
2 | 2 | AI-EL-561~570 | Elective 1 | 2 | 2 |
| AI-CR-504 | Research Methods for intelligent Systems |
1 | `1 | GC-CR-501 | Development Policy | 3 | 3 |
| GC-NC-550 |
Entrepreneurship, Scientific Communication and Leadership (4hr) |
0 | 0 | AI-NC-553 |
Case Studies in Ethics and Fairness in AI (1hr) |
0 | 0 |
| AI-TH-699 | Thesis | 0 | 0 | AI-TH-699 | Thesis | 4 | 4 |
| Semester III | Semester IV | ||||||
| Course Code | Course Title | MAS | PhD | Course Code | Course Title | MAS | PhD |
| AI-CR-601 | Advanced Topics in Deep Learning |
3 | 3 | AI-TH-699 | Thesis | 13 | 13 |
| AI-EL-561~570 | Elective II | 2 | AI-EL-561-570 | Elective III | 2 | ||
| AI-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 | OA-TH-699 | Thesis | 11 | ||
| Total credit for Thesis = 30 credit | |||||||
| Total credit for Master in Applied Sciences course= 52 credit (18 credit core course + 2 credit Technical elective + 2 credit group project + 30 credit Thesis) | |||||||
| Total credit for Thesis = 50 credit | |||||||
| Total credit for Ph.D in Applied Sciences course= 76 credit (18 credit core course + 6 credit Technical elective + 2 credit group project + 50 credit Thesis) | |||||||
| Semester I | Semester II | Semester III | Semester IV |
|
3 Core Course 1 Non-Credit Course Group formation, project assignment and initiation of project |
3 Core Course 1 Non-Credit Course 1 Technical Elective Continuation and Submission of Group project Proposal submission to Advisory Committee |
Thesis Work Initiation and Thesis Progress Presentation |
Comprehensive Exam Thesis Defense |
| Semester I | Semester II | Semester III | Semester IV | Semester V | Semester VI |
|
• 3 Core Course • 1 Non-Credit Course • Group formation, project assignment and initiation of project |
• 3 Core Course • 1 Non-Credit Course • 1 Technical Elective • Continuation and Submission of Group project |
• 1 Core Course • 1 Technical Elective • Proposal submission to Advisory Committee |
• 1 Technical Elective • Thesis Work Initiation and Thesis Progress Presentation |
• Thesis Work Initiation and Thesis Progress Presentation |
• Comprehensive Exam • Thesis Defense |