Skill
Fine-tuning basics
When prompting is not enough. Data quality beats parameter count.
Do these first
What you will be able to do
- Decide when not to fine-tune
- Format instruction data
- Evaluate against a frozen baseline
Curated resources
Start with the pick, then branch out
Scores are LearnPath editorial opinions (clarity, cost, freshness, project density) — not an objective ranking. Every YouTube item is embedded officially after a click-to-load facade.
Official docs
LearnPath pickinteractiveintermediate
Hugging Face NLP course
Hugging Face8h
Free. Chapters 1–4 cover the stack you will actually use.
Score 94
OpenOfficial docs
Official docsdocumentationintermediate
PyTorch tutorials
PyTorch3h
Official basics track. Run locally or in Colab.
Score 95
Open
11h 56mLearnPath pickMore curatedyoutube courseadvanced
LLM Fine-Tuning Course – From Supervised FT to RLHF, LoRA, and Multimodal
freeCodeCamp.org11h 56m
Twelve hours published in 2026 covering the full adaptation spectrum — supervised fine-tuning, LoRA/QLoRA, RLHF and DPO, up to multimodal models. The most complete and most current fine-tuning resource verified.
Score 86
Watch
3h 29mAdvancedMore curatedyoutube videoadvanced
Train Your Own LLM – Tutorial
freeCodeCamp.org3h 29m
A 2025 tutorial that trains a small language model on your own data — tokeniser, dataset preparation, training loop, evaluation. Demystifies 'training a model' without requiring a cluster.
Score 81
Watch