awesome-ai-engineering

Overview of awesome-ai-engineering

What it is

This repository is a curated collection of artificial intelligence engineering resources, roadmaps, tools, and projects. It covers topics such as large language models (LLMs), retrieval-augmented generation (RAG), AI agents, the Model Context Protocol (MCP), fine-tuning, evaluations, and production AI systems. The collection is intended to help students, professionals, and developers discover learning materials, tools, and opportunities.

Key features

• Categorized resources for AI and machine learning, including courses, GitHub repositories, and research papers.
• A quick start guide for beginners and sections for trending technologies like Web3, AI, and cybersecurity.
• Lists of popular AI tools (e.g., ChatGPT, Midjourney) and directories of AI tools.
• Sub-sections for large language models, deep learning, and related topics with online courses and playgrounds.
• Resources for programming languages such as Python, with tutorials and cheat sheets.
• Information on student programs, hackathons, competitions, and free learning resources.

Use cases

This repository is suitable for college students and working professionals seeking to learn new coding languages, find opportunities like hackathons and conferences, or explore AI engineering topics. It can be used as a reference for discovering curated learning materials, tools, and community resources in AI and related fields.

Getting started

To use this resource, browse the table of contents in the repository for categories such as “AI Tools and Resources” or “Programming Languages & Frameworks.” Follow links to external courses, tools, and platforms as listed. For specific installation or usage instructions, see the respective tool or project’s own documentation.

License and pricing

This repository is licensed under the MIT License. It is open source and free to use.

Based on the project's public README and repository metadata.