Awesome AI Agents › Courses and Tutorials
Awesome AI Apps is a collection of working example applications that show how AI agents and generative AI features are assembled in practice. Unlike a link-only awesome list, each entry is a complete project directory inside the repository with its own code and setup instructions, so the list doubles as a reference implementation library. The material is organised into five sections. Starter agents are small single-purpose programs that demonstrate one integration at a time, such as a chat assistant on the OpenAI API, a Claude conversation agent, a Google model chat, a local Llama chat, a Together AI streaming chatbot, a voice-enabled assistant using ElevenLabs, and a code reviewer driven by a Claude model. Advanced agents cover multi-step reasoning workflows such as brand video monitoring and generating blog posts from video with a multi-agent pipeline. Multi-agent teams show several specialised agents cooperating on one task, for example a content creation team. The RAG section contains retrieval-augmented applications including contextual and corrective video RAG with semantic retrieval and tiered evaluation, a RAG-backed content management system, and a competitive intelligence platform. Multimodal apps combine text, images, audio and video, with examples for video analysis, sketch-to-video generation, a chatbot that accepts text, images and video, and live avatar demos. Because the examples deliberately span different stacks, readers can compare how the same idea is expressed with hosted APIs from OpenAI, Anthropic and Google, with local models, and with different agent frameworks. The repository publishes a roadmap describing a daily release cadence and a target number of applications. It suits developers who want a starting point they can copy and adapt rather than framework documentation.
https://github.com/rohitg00/awesome-ai-apps
A comprehensive guide and resource hub for prompt engineering, context engineering, retrieval-augmented generation, and AI agents, offering tutorials, papers, tools, and courses to optimize the use of large language models.
Learn Claude Code is an educational project that teaches how to build modern AI coding agents like Claude Code through a progressive tutorial covering core concepts, planning, subagents, and skills mechanisms.
AI Engineering Hub is a comprehensive repository offering in-depth tutorials and practical resources on Large Language Models, Retrieval-Augmented Generation, and real-world AI agent applications for learners and practitioners.
The Hugging Face Agents Course is a comprehensive educational resource that teaches the fundamentals and advanced concepts of AI agents and large language models through structured units, practical frameworks, and community collaboration.
GenAI_Agents is a comprehensive repository offering tutorials, implementations, and community resources for building and advancing generative AI agents from basic to advanced levels.
This course provides a comprehensive project-based tutorial on Harness Engineering for building reliable AI coding agents, covering environment setup, state management, verification, and control.
An AI-powered tool that analyzes GitHub repositories and generates beginner-friendly tutorials with visualizations to simplify understanding complex codebases.
A comprehensive guide to prepare for machine learning and AI technical interviews at major tech companies, covering coding, ML fundamentals, system design, and behavioral aspects.