LLM Engineering: Prompting, Fine-Tuning, Optimization & RAG
About this course
This specialization teaches end-to-end LLM engineering—from prompt design and evaluation to fine-tuning workflows, model optimization, and retrieval-augmented generation (RAG). You’ll learn to build robust LLM applications with measurable quality, safer outputs, and cost-aware performance using modern tooling such as LangChain, Hugging Face, and LangGraph. By the end, you’ll be able to design production-ready LLM pipelines that combine prompting, adaptation, and retrieval for real-world use cases.
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What you'll learn
- create effective prompts for LLMs
- implement fine-tuning workflows
- optimize LLM models for performance
- integrate retrieval-augmented generation techniques
- build LLM applications using LangChain and Hugging Face tools
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