Llm-course

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

Install guide (official) ↗ GitHub ↗ Creator kit →

Llm-course at a glance

Checked 21 Oct 2026

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks. Added from the trending feed (owner) on 2026-10-18 with 83,868 GitHub stars. So far only the licence comes from GitHub; the other facts are unknown until someone checks them.

Cite this pageRepoQuarry. “Llm-course.” Checked 21 Oct 2026. https://repoquarry.dev/projects/llm-course

What it replaces

Nothing people pay for: it’s a free tool, listed because people search for it. Find similar projects in Courses and learning.

Facts, with sources

Every answer links to where we found it. We read the documentation; we did not install it.

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QuestionAnswerSourceChecked

Runs on my machine? This is a course with notebooks and linked tools, not one self-hosted app. Local model-running options and hosted notebooks are documented. Evidence summary (paraphrase): This is a course with notebooks and linked tools, not one self-hosted app. Local model-running options and hosted notebooks are documented. raw.githubusercontent.com · README.md ↗ 2d ago

Code licence Apache-2.0 github.com · llm-course#license ↗ 3d ago

Model weights licence No bundled weights; the course is a README with links to notebooks and outside models github.com · llm-course ↗ today

Commercial use Yes, Apache-2.0 allows commercial use Apache License github.com · LICENSE ↗ today

Paid services needed? Reading the course is free. Exercise costs depend on the selected model, API or compute service; no universal paid-service requirement verified. Evidence summary (paraphrase): Reading the course is free. Exercise costs depend on the selected model, API or compute service; no universal paid-service requirement verified. raw.githubusercontent.com · README.md ↗ 2d ago

Hardware Not checked yet Know the answer? —

Operating systems Read in a web browser; notebooks open in Google Colab. No desktop OS list Ultra-efficient supervised fine-tuning in Google Colab. github.com · README.md#-notebooks ↗ today

Setup effort Easy; read online, notebooks open in Google Colab Supervised fine-tune Mistral-7b in a free-tier Google Colab with TRL. github.com · README.md#-notebooks ↗ today

No licence changes since we started watching. Licence watch: follow Llm-course and we email you if its licence terms change.

Growth and activity in detail

Is it popular, and is anyone still working on it? From GitHub.

Compare →

Quiet latelyNo commits in the last 12 weeks.
Few active maintainersOnly 2 people committed in the last 12 months, so its future depends on very few hands.

2 people committing in the last 12 months · 0 pull requests merged in 30 days · 0 issues opened, 0 closed in 30 days

Stars over time

Building history

+317 stars since 19 Oct 2026. The 7-day comparison and the trend label start once there is a full week of daily counts.

Llm-course

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Tracked daily since 19 Oct 2026. Dashed history: estimated from public records of when people starred the repo. Lines connect observations only; gaps contain no measured points.

Commits per week, last 52 weeks

active 0 of the last 12 weeks

No commits in either of the last two 12-week periods.

Busiest week: 2 commits. Focus or tap a bar for its week.

Where these numbers come from

Stars, forks, releases: GitHub's public API, fetched every night (last fetch today).
Star history: counted every night since 19 Oct 2026.
Commits and people committing: GitHub's repository statistics, counted weekly. Names are never stored.
Pull requests and issues: counted from GitHub for the last 30 days.
Stars show popularity, not quality. The facts below are checked separately, by reading the project's own documentation. How we check.