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How to become an AI engineer in 100 days

Course

100 Days of AI Engineering

Beginner to Advanced 100 days · 57 lessons published English & Hindi

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How to become an AI engineer in 100 days

How to become an AI engineer in 100 days

What this lesson covers

An AI engineer is not a researcher. You are not training models — you are building systems around them: calling APIs, managing context, giving models tools, deciding when to stop a loop, and handling the fact that the thing at the centre of your system is non-deterministic. That last part is what makes this different from ordinary backend work, and it is why the course spends twenty days building agents by hand. When your agent loops forever or calls the wrong tool, no framework will explain why. Having written the loop yourself will. The order: foundations, prompting, APIs, agents from scratch, then LangChain and LangGraph. Frameworks last, on purpose.

The code

main.pyPython
Set your API key first, then run it.

The most common way to stall on this course is to skip the code and only watch. Every lesson has something to run — run it, then break it deliberately and read the error. That is the whole skill.

Build this yourself

Each task uses only what this lesson and the earlier ones covered. Do them in order — the third is usually the one that teaches you something.

  1. Install the packages above and confirm the script prints 'ready' for both.
  2. Create a project folder with a .env file and add it to .gitignore now, before there is a key in it.
  3. Write down what you want to have built by Day 100. Check it on Day 30.

Before you move on

If your environment works today, no lesson from here on will stall on setup.