A free 21-lesson Microsoft course that goes from generative AI basics and prompting to working applications. Each lesson ships with code.
Awesome lists & learningShubhamsaboo
awesome-llm-apps
A large collection of ready-made LLM apps: agents, RAG systems and skills for coding agents. Every template can be run and taken apart piece by piece.
Who it is for
For people who learn from working examples and want to ship a first agent quickly.
How to start
- Clone the repo:
git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git - Open a starter template:
cd awesome-llm-apps/starter_ai_agents/ai_travel_agentand install dependencies:pip install -r requirements.txt - Run the app:
streamlit run travel_agent.py
Steps are taken from the README. Check the current version in the repository before running them.
Stars over the last 30 days
Author's description
100+ AI Agents, Agent Skills and RAG Apps - Free and Open Source.
More in «Awesome lists & learning»
Code for Sebastian Raschka's book: you build a GPT-like model in PyTorch step by step, then pretrain and finetune it. The best way to see how an LLM works inside.
An animation engine Grant Sanderson uses to make 3Blue1Brown videos, including the well-known neural network ones. It is not an AI library but a tool for explaining math and ML visually.
A 12-week course on classic machine learning: 26 lessons and 52 quizzes. The foundation that makes modern models easier to understand.
A three-part LLM roadmap: fundamentals, the LLM Scientist (building models) and the LLM Engineer (building apps). Topics come with Colab notebooks.
A Microsoft course of 18 lessons on building AI agents: tools, memory, planning, multiple agents. Code examples live in the code_samples folder.
