# The maths ML actually uses

Source: https://freeaicourses.com/paths/maths-for-ml

## Steps

### Step 1: Machine Learning Crash Course

Introduces the maths visually before you need to derive anything by hand.

You recognise gradients, loss surfaces and matrices in context.

### Step 2: CS50's Introduction to AI with Python

Applies probability and optimisation to real algorithms so the maths has a purpose.

You can follow the maths in most intermediate ML courses.

## Related pages

- [Machine Learning Crash Course](https://freeaicourses.com/courses/machine-learning-crash-course)
- [CS50's Introduction to AI with Python](https://freeaicourses.com/courses/cs50-ai)
- [AI learning paths free to follow](https://freeaicourses.com/paths)
- [All free AI courses, rated](https://freeaicourses.com/courses)
- [AI learning path for non-coders](https://freeaicourses.com/paths/ai-for-non-coders)
- [Use AI tools well at work](https://freeaicourses.com/paths/ai-at-work)
- [Python for AI, from zero](https://freeaicourses.com/paths/python-for-ai)
- [Machine learning foundations](https://freeaicourses.com/paths/ml-foundations)
- [Deep learning, hands-on](https://freeaicourses.com/paths/deep-learning)
- [Build apps with LLMs](https://freeaicourses.com/paths/build-with-llms)
- [Become an ML engineer](https://freeaicourses.com/paths/ml-engineer)
- [From data analysis to AI](https://freeaicourses.com/paths/data-science-to-ai)
- [Google](https://freeaicourses.com/platforms/google)
- [Harvard CS50](https://freeaicourses.com/platforms/harvard-cs50)