MS Data Science
Build the skills to lead in MS Data Science
The MS Data Science program at Superior University is designed to support the lifelong learning of students, enabling them to accelerate or redirect their careers with a strong emphasis on network analysis, text analysis, machine vision, and AI. The program also addresses the needs of students looking to pursue a PhD as the curriculum takes into account current research, the dynamics of the latest industrial practices, and the exploration of social contexts, leadership, and ethical considerations.
Eligibility Criteria
Degree in relevant subject, earned from a recognized university after 16 years of education with at least 60% marks or CGPA of at least 2.0 (on a scale of 4.0). Qualify GAT Test General (NTS) with 50% or GAT Test (University) with 60%.
- Total credit hours: 30
- Semester: 4
- Course duration: 2 years
Semester 1
| Course | Credit Hours |
|---|---|
| Machine Learning | 3 |
| Research Methods | 3 |
| Elective-I | 3 |
| Elective-II | 3 |
| Total | 12 |
Semester 2
| Course | Credit Hours |
|---|---|
| Statistical and Mathematical Methods | 3 |
| Tools and Techniques and Data Science | 3 |
| Elective-III | 3 |
| Elective-IV | 3 |
| Total | 12 |
Semester 3&4
| Course | Credit Hours |
|---|---|
| Thesis | 6 |
| Total | 6 |
List of Electives
| Courses | Credit Hours |
|---|---|
| Advanced Computer Vision | 3 |
| Machine Learning | 3 |
| Applied Image Processing | 3 |
| Big Data Analytics | 3 |
| Advanced Data Science | 3 |
| Cloud computing | 3 |
| Data Visualization | 3 |
| Deep Learning | 3 |
| Deep Reinforcement Learning | 3 |
| Natural Language Processing | 3 |
| Social network analysis | 3 |
| Time-series Analysis and Prediction | 3 |
| Total | 36 |
*To accommodate modern trends, Institute may reserve the right to change course requirements, fees, course classifications, course contents, class schedules, venues, faculty and the like, whenever it deems appropriate.
