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• To equip students to transform data into actionable insights to make complex business decisions
• To enable students, understand and analyze a problem and arrive at computable solutions
• To expose students to the set of technologies that match those solutions
• To gain hands-on experience on data-centric tools for statistical analysis, visualization and big data applications at the same rigorous scale as in a practical data science project
• To understand the implications of handling data in terms of data security and business ethics
The amount of data is growing so rapidly and their significance in the emerging societal set ups such as the pervasive Internet of Things. The way one imagines data is going to change in the coming years. Both Big Data Analytics and pervasive computing hinge on the principle axis of data analytics. MS (DS) program is going to be relevant in terms of job creation and artisanal smart business generation. Graduates from this program would definitely avail the early-bird advantage.
| Course Code | Course Title | Credit Hours |
|---|---|---|
| DS-711 | Statistical and Mathematical Methods for Data Science | 3(3+0) |
| DS-712 | Tools and Techniques in Data Science | 3(2+1) |
| DS-713 | Data Visualization | 3(3+0) |
| Credit Hours | 9 |
| Course Code | Course Title | Credit Hours |
|---|---|---|
| DS-721 | Machine Learning | 3(3+0) |
| DS-722 | Big Data Analytics | 3(3+0) |
| DS-723 | Deep Learning | 3(3+0) |
| Credit Hours | 9 |
| Course Code | Course Title | Credit Hours |
|---|---|---|
| DS-731 | MS Thesis-I | 3(0+3) |
| DS-732 | Social Network Analysis | 3(3+0) |
| Credit Hours | 6 |
| Course Code | Course Title | Credit Hours |
|---|---|---|
| DS-741 | MS Thesis-II | 3(0+3) |
| DS-742 | Time Series Analysis and Prediction | 3(3+0) |
| Credit Hours | 6 | |
| Total Credit Hours | 30 | |
