Awesome AI Agents › Courses and Tutorials
Learn Harness Engineering is a detailed, project-based course designed to teach the principles and practices of building robust environments for AI coding agents. The course emphasizes that even the most advanced AI models require a proper 'harness' to perform real-world engineering tasks reliably. Drawing on theories and practices from leading AI research institutions like OpenAI and Anthropic, this tutorial addresses common problems such as context loss and premature task completion in multi-turn AI agent development. The curriculum includes 12 lectures and 6 practical projects, guiding learners through critical aspects of harness design, including creating instructional frameworks, defining operational scope, managing agent state, implementing verification workflows (tests, linting, type-checking), and handling lifecycle management. The course highlights the significant difference a well-designed harness can make, transforming unreliable model performance into consistent, functional outcomes, as demonstrated by case studies where a harness drastically improved output quality and efficiency. Key features include a course homepage, immersive lectures with hands-on projects, and a ready-to-use resource library offering templates and reference configurations. The repository also provides a 'harness-creator' skill to quickly scaffold production-grade harnesses. Available in 14 languages, this course is an essential resource for developers looking to master the engineering environment required for AI agents to operate effectively and reliably.
https://github.com/walkinglabs/learn-harness-engineering
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.
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.
A trilingual (Traditional Chinese, English, Simplified Chinese) learning roadmap for agentic AI, offering 240+ curated resources and hands-on examples from LLM basics to multi-agent systems.