The Master of Science (MS) in Data Science and Artificial Intelligence program at South Asian University, Delhi, is an innovative course designed for students passionate about the emerging fields of data science and AI. This program provides a thorough understanding of data analytics, machine learning, artificial intelligence, and other allied subjects, equipping students with the essential skills to excel in the digital age.
Hosted through SAU’s virtual campus, the program offers both flexibility and accessibility, making it ideally suited for learners seeking to balance their education with various other commitments. By combining theoretical knowledge with hands-on projects, students acquire the practical expertise needed to solve complex challenges and drive innovation.
The curriculum is designed to align with industry demands, preparing students for a variety of roles in data science, AI development, and research. Enrol in SAU’s MS (DS and AI) program to join the next generation of tech leaders to study and innovate data-driven solutions and artificial intelligence.
* Students without minimum two mathematics courses must take an add-on course, “Foundation of Mathematics,” in the first semester.
Minimum: 2 Years | Maximum: 4 Years
| Types of Fee | Amount |
|---|---|
| Registration Fee | USD 20.00 / INR 1740.00 (One Time) |
| Tuition Fee | USD 550.00 / INR 47,850.00 (Per Semester) |
| Admission Fee | USD 200.00 / INR 17,400.00 (One Time) |
| Student Aid Fund | USD 10.00 / INR 870.00 (Per Semester) |
Scholarship: 25% tuition fee concession is available for:
Click here to read Refund Policy of MS (Data Science and Artificial Intelligence)
The installment policy for all virtual campus degree programmes follows SAU’s standard policy.
A candidate who meets the eligibility criteria can enroll in the programme.
|
Semester |
Courses |
Credits |
|
I |
Data Analysis and Visualization |
4 |
|
Probability & Statistics for Machine Learning |
4 |
|
|
Machine Learning techniques |
4 |
|
|
Linear Algebra for Machine Learning |
4 |
|
|
Introduction to Artificial Intelligence |
4 |
|
|
II |
Data Engineering |
4 |
|
Deep Learning |
4 |
|
|
Big Data Analytics |
4 |
|
|
Data and AI Ethics |
4 |
|
|
Computer Vision |
4 |
|
|
III |
Generative AI |
4 |
|
Natural Language Processing |
4 |
|
|
Quantum Machine Learning |
4 |
|
|
AI in Cybersecurity |
4 |
|
|
Elective-1 |
4 |
|
|
IV |
Elective-2 |
4 |
|
Elective-3 |
4 |
|
|
Dissertation |
12 |
List of Elective Courses:
Disclaimer:
