Description

This eight-week course is designed for students who want to understand the fundamentals and concepts behind AI and machine learning. Every class will be a lecture, followed by notebooks for homework that apply concepts learned in class. The lecture will take up all of class time; however, there will be a section at the beginning of each class allowing students to ask questions about the homework.

Syllabus

1. Basics of Machine Learning, Supervised vs. Unsupervised Learning
2. Neural Networks and Gradient Descent
3. Popular Machine Learning Algorithms
4. Convolutional Neural Networks and Computer Vision
5. LLMs
6. Reinforcement Learning
7. Advancements Right Now
8. Real-World Strategies & Best Practices for ML