Fine-Tuning & Model Adaptation
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10 lessons3 levels1 capstone project
Know when prompting/RAG are insufficient; master supervised fine-tuning, LoRA/PEFT, data preparation, evaluation, overfitting, post- training, deployment tradeoffs, and adaptation-vs-retrieval decisions.
BASIC
- Fine- tuning Open LLMs on GKE — Google Cloud Tech (7 min)
Current production view of why fine-tuning matters and the infrastructure/data/workflow gap. - Introduction to Large Language Models — Google Cloud Tech (15 min selected)
Places tuning alongside prompting and foundation- model application patterns. - Generative AI for Beginners — Microsoft Developer (25 min selected)
Use the fine-tuning/model- adaptation chapters for the developer workflow and tradeoffs.
INTERMEDIATE
- RAG From Scratch: Part 1 (Overview) — LangChain
Apply Fine-Tuning & Model Adaptation through the adjacent capability: Retrieval-Augmented Generation (RAG). - What Is Retrieval-Augmented Generation (RAG)? — IBM Technology
Apply Fine-Tuning & Model Adaptation through the adjacent capability: Retrieval-Augmented Generation (RAG). - Multimodal AI — Google Cloud Tech
Apply Fine-Tuning & Model Adaptation through the adjacent capability: Multimodal AI.
ADVANCED
- Build an MCP Server in 20 Minutes — pixegami
Extend Fine-Tuning & Model Adaptation into senior/production practice through Tool Use & Function Calling. - MCP Workshop — Anthropic
Extend Fine-Tuning & Model Adaptation into senior/production practice through AI Agents. - Learn RAG From Scratch — freeCodeCamp / LangChain
Extend Fine-Tuning & Model Adaptation into senior/production practice through Retrieval-Augmented Generation (RAG).