| Course number : |
SI-2026-12 |
| Eligible students to participate : |
B.Tech. 2nd year, 3rd year and 1st year MTech and MSc DS |
| Prerequisites : |
Very good Aptitude and Reasoning Skills. Thorough understanding of at least 1 Programming Language (JAVA, PYTHON, C++) |
| Resource person(s) : |
- Ayandeep Ray
- Akash Bhattacharya
- Aritra Sen
- Shamik Banerjee
(Based on Exact dates and availability, one of them will conduct)
|
| Duration of the Course : |
4 weeks – 100 hrs (Theory : 40hrs, Hands-on : 40hrs; Homework :20hrs) |
| Course Outcome : |
- Conceptual clarity on data cleaning, preprocessing and gathering insights.
- Approaching any type of data – structured or unstructured
- Exposure to machine learning algorithms to be industry ready
- Good grasp of Python libraries including advanced ones like TensorFlow and Kera
- Understanding of corporate discipline and nuances
|
| Course Content : |
- Introduction and basics Of Data Science
- Machine Learning Systems and Algorithms
- Training Models
- Support Vector Machines
- Decision Trees
- Ensemble Learning and Random Forests
- Feature engineering and feature selection
- Unsupervised Learning Techniques
- Pipelines
- DEEP Learning
- Mini Project
|
| Methodology of Course Delivery : |
- Online Live Classroom Teaching
- Instructor led Hands-on Lab practices (online)
- Sharing of Class Recordings, Reference Materials, Assignments, Projects
|
| Batch Size : |
50 |
| Course Fees : |
5,500.00/- |
| Residence Fee (optional) : |
0.00/- |