hemansnation/AI-Engineer-Headquarters resource

Health v2 · maintenance only

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Adoption not part of the score

3673 stars · 699 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

An open-source, action-oriented curriculum and learning roadmap for becoming an AI engineer, covering ML, MLOps, LLMs, RAG systems, fine-tuning, and autonomous AI agents. It is organized as a structured drill with deep-work routines, video sessions, and text notes maintained in Jupyter Notebooks.

Use cases

• learn ai engineering from scratch
• roadmap to become an llm engineer
• study machine learning and mlops with a structured curriculum
• learn to build production rag systems
• understand llm fine-tuning and evaluation
• prepare for an ai engineer career
• find a guided study plan for deep learning and nlp

When to choose

• you want a free, structured, self-paced AI engineering curriculum
• you prefer action-oriented learning with notebooks and video sessions
• you want coverage of the full LLM stack including RAG, fine-tuning, agents, and security

When to avoid

• you need production-ready software or a library to import into your codebase
• you want a certified or paid cohort program with mentorship and job placement
• you need a stable, versioned dependency rather than educational content

Facets

learning-resource · maturity active

machine-learning deep-learning llm-inference rag agent-framework nlp data-science artificial-intelligence machine-learning large-language-models tutorials education python cross-platform ai-engineering mlops llm-fine-tuning curriculum langchain langgraph llm-evaluation llm-security career-development jupyter-notebooks retrieval-augmented-generation ai-agents natural-language-processing

Member repositories

For agents

markdown · JSON · MCP: product_card(name="hemansnation/AI-Engineer-Headquarters")