Machine learning foundations

How long does it take?

The steps, in order

1. 1

   Kaggle Intro to Machine Learning

   Kaggle

   Difficulty: 2 of 5

   Why this step: A fast, practical on-ramp if you haven't done it yet.

   You're ready for the next step when: You understand the basic training and validation workflow.

2. 2

   Machine Learning Crash Course

   Google

   Difficulty: 2 of 5

   Why this step: Fills in the concepts properly, with excellent interactive visuals.

   You're ready for the next step when: You can explain loss, gradient descent and overfitting.

3. 3

   CS50's Introduction to AI with Python

   Harvard

   Difficulty: 3 of 5

   Why this step: Builds the algorithms by hand, so nothing is a black box.

   You're ready for the next step when: You can implement core ML and search algorithms from scratch.

Where to go next

• Deep learning, hands-on

  Build and train neural networks for vision and text

• All free AI learning paths

  Every path, with who it suits and how long it takes.

• All free AI courses, rated

  Filter the whole catalogue by level, topic and certificate.

• AI learning path for non-coders

  Explain how modern AI works and use it well at work

• Use AI tools well at work

  Prompt, evaluate output, and automate everyday tasks safely

• Python for AI, from zero

  Write the Python every AI course assumes

• The maths ML actually uses

  Enough linear algebra, calculus and probability to read ML courses without panic

• Build apps with LLMs

  Ship an app that uses an LLM API, retrieval and evaluation

• Become an ML engineer

  Deploy, monitor and maintain models in production

• From data analysis to AI

  Move from spreadsheets and SQL to ML and AI

• Is Kaggle Learn worth it?

  Our review of Kaggle Learn, where steps on this path are hosted.

• Is Google worth it?

  Our review of Google, where steps on this path are hosted.

• Is Harvard CS50 worth it?

  Our review of Harvard CS50, where steps on this path are hosted.