courseraАнализ данных

Boost RAG with Chroma

Курс от Coursera

Средний≈ 3.7 чАнглийский

О курсе

Boost RAG with Chroma is an intermediate, hands-on course designed for developers and AI practitioners who need to solve one of the biggest challenges with Large Language Models: their tendency to hallucinate. This course moves beyond theory and teaches you how to build a practical, effective Retrieval-Augmented Generation (RAG) pipeline to make your LLMs more trustworthy and enterprise-ready. You will learn the architectural patterns for using a vector database to create an external knowledge base that grounds an LLM's responses in verifiable data. Using a project-based approach, you will implement this pattern, drawing on the popular open-source tools Chroma and LangChain as concrete examples. The course culminates in a hands-on evaluation where you will directly compare your model's answers—with and without RAG—to qualitatively measure the improvement in factuality. You'll leave with a portfolio-ready project and the ability to build safer, more reliable generative AI applications using any set of comparable tools.

Навыки, которые вы освоите

Vector Databases LangChain Retrieval-Augmented Generation Large Language Modeling Embeddings AI Orchestration Model Evaluation LLM Application Generative AI

Программа курса

2 модулей · 11 учебных материалов

01Building the RAG Pipeline6 материалов

The High Cost of Trusting LLMsDIALOGUE From Hallucination to Reality: Grounding AI with RAGВидео The RAG Architecture ExplainedЧтение Building a RAG Pipeline with LangChain and ChromaВидео

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