MSc Data Science program revolves around major disciplines of Calculus, C-Programming, and Descriptive Statistics. Latest technologies such as Python, ML, DL, and Spark are also taught thoroughly in the program.
The semester-wise syllabus for Data Science is as follows.
| Semester I | Semester II |
| Mathematics for Spatial Science | Spatial Big Data and Storage Analytics |
| Applied Statistics | Data Mining and Algorithms |
| Fundamentals of Data Science | Machine Learning |
| Python Programming | Advanced Python Programming for Spatial Analytics |
| Introduction to Geospatial Technology | Image Analytics |
| Programming for Spatial Sciences | Spatial Data Base Management |
| Business Communication | Flexi-Credit Course |
| Cyber Security | - |
| Integrated Disaster Management | - |
| Semester III | Semester IV |
| Spatial Modeling | Industry Project |
| Summer Project | Research Work |
| Web Analytics | - |
| Artificial Intelligence | - |
| Flexi-Credit Course | - |
| Predictive Analytics and Development | - |
There are electives as well which you need need to choose to complete your credits. Usually, the electives on offer for Data Science are as follows.
| MSc Data Science Electives | |
| Deep Learning | IOT Spatial Analytics |
| System Dynamic Simulation | Spatial User Interface Design and Implementation |
| Genomics | Research Modeling and Implementation |
| Multivariate Analysis | Programming for Data Science |
| Stochastic Process | Hadoop |
| Image and Video Analytics | Internet of Things |
| Exploratory Data Analysis | Identification of Data Collection |
Python Programming, Deep Learning, R Programming, Cloud Programming, Multivariate Analysis are some of the common Data Science subjects.