| Module | Topic | Time (IST) | Duration |
| Pre-Work (6-8 Hrs.) | intro to the World of AI | 3-5PM | 2 Hrs. |
| | Mathematics & Statistics Behind Ai | 3-5PM | 2 Hrs. |
| | Ai Application Case Study #1 | 3-5PM | 2 Hrs. |
| | | | |
| Python Found: (12-16 Hrs.) | Introduction to Python | 3-5PM | 2 Hrs. |
| | Python introduction for Data Science | 3-5PM | 2 Hrs. |
| | Ai Application Case Study #2 | 3-5PM | 2 Hrs. |
| | Data Visualization | 3-5PM | 2 Hrs. |
| | Exploratory Data Analysis | 3-5PM | 2 Hrs. |
| | Ai Application Case Study #3 | 3-5PM | 2 Hrs. |
| | | | |
| Machine Learning (12-16 Hrs.) | Intro to Supervised Learning- Linear Regression | 3-5PM | 2 Hrs. |
| | Intro to Supervised Learning Classification | 3-5PM | 2 Hrs. |
| | Decision Trees | 3-5PM | 2 Hrs. |
| | Ai Application Case Study #4 | 3-5PM | 2 Hrs. |
| | K-means Clustering and Support Vector Regression | 3-5PM | 2 Hrs. |
| | Ai Application Case Study #5 | 3-5PM | 2 Hrs. |
| | | | |
| Advanced ML (10-14 Hrs.) | Bagging and Random Forest | 3-5PM | 2 Hrs. |
| | Ai Application Case Study #6 | 3-5PM | 2 Hrs. |
| | Boosting | 3-5PM | 2 Hrs. |
| | Model Tuning and deployment for Decision Trees and Support Vector Regression | 3-5PM | 2 Hrs. |
| | Ai Application Case Study #7 | 3-5PM | 2 Hrs. |
