1. Understanding AI History
2. Setting up Python Workflow for AI Development
3. Python Libraries for Data Scientists
4. Foundational Concepts for Effective Neural Network Training
5. Dimensionality Reduction, Unsupervised Learning and Optimizations
6. Building Deep Neural Networks from Scratch
7. Derivatives, Backpropagation, and Optimizers
8. Understanding Convolution and CNN Architectures
9. Understanding Basics of TensorFlow and Keras
10. Building End-to-end Image Segmentation Pipeline
11. Latest Advancements in AI