ed-donner/llm_engineering resource

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7157 stars · 7002 forks observed · 2026-08-28

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

A companion repository of Jupyter Notebook exercises and projects for Ed Donner's 'Mastering LLM Engineering' course, an 8-week program covering building applications with large language models. It includes hands-on projects using tools like Ollama and Llama 3.2, progressing from basics to advanced LLM engineering techniques.

Use cases

• learn llm engineering from scratch
• build projects with local llms using ollama
• follow an 8-week structured llm course
• practice building rag and agent applications
• get started with llama 3.2 on a home computer
• supplement a udemy course with runnable notebooks

When to choose

• you want a structured, project-based path to learning LLM engineering
• you prefer hands-on Jupyter notebooks over reference documentation
• you want to run local models like Llama 3.2 with Ollama
• you are taking or considering the accompanying Udemy course

When to avoid

• you need production-ready LLM tooling rather than educational material
• you want a maintained library with an API instead of course code
• you cannot run local models and lack API access to commercial LLMs

Facets

learning-resource · maturity active

llm-inference rag agent-framework prompt-engineering machine-learning large-language-models artificial-intelligence tutorials education developer-tools python cross-platform self-hosted course-materials jupyter-notebooks udemy-course ollama hands-on-projects llm-engineering

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