Course Introduction

This is the repo for the AI elective course at RDFZ, taught by Shao (Me) and Michael (My good friend). This course aims to provide a fun introduction to understanding and using AI, combining theoretical concepts with projects. This is by no means a formal and comprehensive course about AI, and it's best used alongside other more formal courses. The goal here is to make things simple, intuitive, and fun.

In this course, we want you to have two takeaways: The first one is straightforward: understanding how AI models work. Apart from that, we also want you to learn how to properly use AI tools in applications such as coding. Learning AI and learning to use AI is super useful!

The repo is still under construction, so if you find any issues, please let me know!

Table of Contents

Class 1: A Gentle Intro to AI

Class 2: Neural Network Basics

Class 3: CNNs

Class 4: Gomoku AI with CNN

Class 5: RNNs

Class 6: Word Embeddings and Transformers

Class 7: Applying LLMs

More classes coming soon!

Visualizations

These are some of the intuitive visualizations we created for explaining various concepts:

How Does A Neural Network Work (Explaination of Weights, Biases, and Activation Functions)

NN Training Visualizer

Convolution Visualizer

AI is changing the world, and we believe everyone should have a chance to understand and use it.