Part 1
- Module 1: Introduction to AI
- What is AI? History and Evolution
- AI vs Machine Learning vs Deep Learning vs Generative AI
- Real-world Applications of AI (healthcare, robotics, recommendation engine, etc.)
- Responsible AI
- Module 2: Python for AI
- Quick Python refresher (data types, control structures, libraries)
- NumPy, Pandas, Matplotlib for data handling and visualization
- Module 3: Data Handling and Preprocessing
- Data is the new oil- understanding importance of data & IT security, basics of data engineering
- Understanding data types: structured, unstructured
- Exploratory Data Analysis
- Data Pre-Processing and Feature engineering
- Splitting datasets (train/test/validation)