Learn ML, LLMs and AI this year — new Guide for 2024

So, you want to learn AI? But you don’t know how or where to get started?

To escape tutorial hell and really learn, you have to get hands-on, write algorithms from scratch, implement papers, and do fun side projects using AI to solve problems.

This article attempts to craft a free curriculum that follows that philosophy.

Also, leave a comment if you think it’s missing anything!

But first, a few notes on the curriculum and some advice on learning.

Top-down approach

This curriculum follows a top-down approach — code first, theory later.

If you like to learn out of necessity. So, if You have to figure out something, a problem to solve, or a prototype to make, may be you will reach far and wide for the information you need, study, make sense of it, and then act on it.

For example, if you want to be an AI engineer who understands LLMs at a fundamental level, which involves having the skill to code transformers from scratch and fine-tuning LLMs on GPUs, etc. May be you can’t do that now because there are gaps in your knowledge, but if you want to fill in those gaps.

Here are the two important things before you start learning anything.