STRUCTURE OF MSDS PROGRAMME
Course Summary
| Course Types | No. of Courses | Cumulative Credit Hours |
|---|---|---|
| Core Courses | 3 | 9 |
| Specialized Courses | 2 | 6 |
| Compulsory Course | 1 | 3 |
| Elective | 2 | 6 |
| Thesis | 2 | 6 |
| Total | 10 | 30 |
Core Courses (9 Credit Hours)
| Course Code | Title | Credit Hours |
|---|---|---|
| DSC7101 | Tools and Techniques in Data Science | 2-1-3 |
| DSC7102 | Statistical and Mathematical Methods for Data Science | 3-0-3 |
| DSC7103 | Machine Learning | 3-0-3 |
| Total | 9 | |
*2+1 means 2 hours of lecture + 3 hours of lab work
Compulsory Course (3 Credit Hours)
| Course Code | Title | Credit Hours |
|---|---|---|
| CC7101 | Research Methodology | 3-0-3 |
| Total | 3 | |
Specialized Courses (6 Credit Hours)
| Course Code | Title | Credit Hours |
|---|---|---|
| DSS7201 | Big Data Analytics | 3-0-3 |
| DSS7202 | Deep Learning | 3-0-3 |
| DSS7203 | Natural Language Processing | 3-0-3 |
| DSS7204 | Distributed Data Processing | 3-0-3 |
| Total (Any Two Courses) | 6 | |
Core Courses (9 Credit Hours)
| Course Code | Title | Credit Hours |
|---|---|---|
| DSC7101 | Tools and Techniques in Data Science | 2-1-3 |
| DSC7102 | Statistical and Mathematical Methods for Data Science | 3-0-3 |
| DSC7103 | Machine Learning | 3-0-3 |
| Total | 9 | |
*2+1 means 2 hours of lecture + 3 hours of lab work
Compulsory Course (3 Credit Hours)
| Course Code | Title | Credit Hours |
|---|---|---|
| CC7101 | Research Methodology | 3-0-3 |
| Total | 3 | |
Specialized Courses (6 Credit Hours)
| Course Code | Title | Credit Hours |
|---|---|---|
| DSS7201 | Big Data Analytics | 3-0-3 |
| DSS7202 | Deep Learning | 3-0-3 |
| DSS7203 | Natural Language Processing | 3-0-3 |
| DSS7204 | Distributed Data Processing | 3-0-3 |
| Total (Any Two Courses) | 6 | |
Elective Courses
| Course Code | Title | Credit Hours |
|---|---|---|
| CSE7209 | Cloud Computing | 3-0-3 |
| DSE7201 | Data Visualization | 3-0-3 |
| DSE7202 | Pattern Recognition | 3-0-3 |
| DSE7203 | Advanced Computer Vision | 3-0-3 |
| DSE7204 | Advanced Topics in Decision Support Systems | 3-0-3 |
| DSE7205 | Algorithmic Trading | 3-0-3 |
| DSE7206 | Bayesian Data Analysis | 3-0-3 |
| DSE7207 | Bioinformatics | 3-0-3 |
| DSE7208 | Business Context Modeling | 3-0-3 |
| DSE7209 | Computational Genomics | 3-0-3 |
| DSE7210 | Data Science in Cyber Security | 3-0-3 |
| DSE7211 | Data Science with R | 3-0-3 |
| DSE7212 | Deep Reinforcement Learning | 3-0-3 |
| DSE7213 | Graph Analytics for Big Data | 3-0-3 |
| DSE7214 | High Performance Computing | 3-0-3 |
| DSE7215 | Implementing Predictive Analysis | 3-0-3 |
| DSE7216 | Inference & Representation | 3-0-3 |
| CSE7212 | IoT for Smart Cities and Smart Homes | 3-0-3 |
| DSE7217 | Mining Massive Datasets | 3-0-3 |
| DSE7218 | Probabilistic Graphical Models | 3-0-3 |
| DSE7219 | Python Programming for Data Science | 3-0-3 |
| DSE7220 | Scientific Computing in Finance | 3-0-3 |
| CSE7207 | Social Network Analysis | 3-0-3 |
| DSE7221 | Text Mining | 3-0-3 |
| DSE7222 | Time Series Analysis and Prediction | 3-0-3 |
Note: The list of elective courses can be extended.
| Research Work/Thesis (6 Credit Hours) | ||
Registration in “MS Thesis – I” is allowed provided the student has
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