Unit	Topic	Description
0	0_onboarding	Welcome, guidelines, necessary tools, and course overview.
1	1_introduction_to_concepts	Definition of agents, LLMs, model family tree, and special tokens.
2	2_frameworks	Overview of Smolagents, LangChain, LangGraph, and LlamaIndex.
3	3_use_cases	SQL, code, retrieval, and on-device agents using various frameworks.
4	4_final_assignment_with_benchmark	Automated evaluation of agents and leaderboard with student results.

Prerequisites

Basic knowledge of Python
Basic knowledge of LLMs

Contribution Guidelines

If you want to contribute to this course, you're welcome to do so. Feel free to open an issue or join the discussion in the Discord. For specific contributions, here are some guidelines:

Small typo and grammar fixes

If you find a small typo or grammar mistake, please fix it yourself and submit a pull request. This is very helpful for the students.

New unit

If you want to add a new unit, please create an issue in the repository, describe the unit, and why it should be added. We will discuss it and if it's a good addition, we can collaborate on it.

Work on existing units

We are actively working on the units and if you want to join us, we will need to find a place in the workflow. Here's an overview of where we are open to collaboration:

Unit	Status	Contributions
0	✅ Complete	Bug fixes and improvements only
1	🚧 In Progress	Work is underway, no need for help with content
2	🚧 In Progress	If you're a contributor to a framework, we're open to contributions and reviews
3	🗓️ Planned	If you're experienced with agents, we're open to help with use cases
4	🚧 In Progress	Work is underway, no need for help with integration

If in doubt, join the discussion in the Discord.