This course will always be free. It covers the foundations of modern Machine Learning and the key concepts that everyone should be familiar with. For those looking to dive even deeper and receive personalized instruction, I also offer an exclusive ML Community. However, I recommend having exposure to the concepts in Generative LLMs before joining the ML Community!

While you don't need to finish the course, I would recommend having exposure to the topics in Generative LLMs before joining the ML Community. Many of the topics we teach in the ML Community build on topics from Generative LLMs. However, those looking to get questions answered 1:1 and receive guidance while completing Generative LLMs are welcome and encouraged to join!

For every lecture, I have created a free coding exercise. You can implement the concept (Linear Regression, Image Recognition, Transformers, etc.) in Python, and then run your code against the provided test cases! Implementing an ML concept is the best way to ensure a deep understanding.

Most ML courses focus on an excessive amount of calculus. The only prerequisites to Generative LLMs are a basic understanding of Python, as well as basic calculus. For example, you should understand how to find the derivative of x². Extremely complicated derivatives are not actually required to build a strong intuition for ML algorithms! Submit your email below to start building your intuitive understanding of ML.