Module 1: Programming Foundations of AI

- Python fundamentals (variables, data types, loops, functions) 

- Functions, Higher-order functions, Numpy

- Pandas and Matplotlib

- Introduction to data handling

Module 2: Machine Learning Algorithms

- Supervised Learning : Regression and Classification

- Unsupervised Learning : Clustering and Dimensionality Reduction

- Ensemble Methods : Random Forests and XGBoost

- Dimensionality Reduction (PCA) and Techniques

Module 3: Neural Networks & Deep Learning

- Neurons and Layers, Weights and Biases

- Activation Functions and Loss Functions

- Generative Adversarial Networks (GANs)

- Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNN)

Module 4: Computer Vision and NLP

- Computer Vision (Classification, Object Detection and Object Segmentation)

- Speech Processing (Problems and Methodologies)

- Natural Language Processing (NLP) (Problems and Methodologies)

Module 5:  Lab Activities and Capstone Preparation

- Transfer learning with pre-trained models

- Build end-to-end capstone projects 

- Create industry level project with real datasets

Module 6:  Capstone Project

- Get Certificate with the Capstone project