AI and Machine Learning

• Python Basics: Variables, Logic, Loops, Functions, Classes

• Linear and Logistic Regression: Mathematics and Implementation

• Perceptron/Naive Bayes Algorithm: Simple Neural Network Fundamentals and Implementation

• Recurrent Neural Networks/LSTMs: Time-Series based Networks

• Convolutional Neural Networks: Image-Based Networks

• Generative Adversarial Networks: Generating Algorithms

We will be covering both the theory behind each of these networks and their implementation in Python through Google Colab. We will also be creating projects such as stock market prediction networks, chatbots, object detection software, and much more.

Prerequisites and Suggested Age Group