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This immersive 2-day Public Training will train participants how to build retriever-based LLM applications using RAG techniques. Over the period of 2 days, students will learn how to set up vector databases, ingest and index documents, rank the retrieved documents, and generate the final output. At the course’s end, learners can build an RAG application using Streamlit, LangChain, Llamaindex, and LLMs.
Understand the fundamental knowledge of Retrieval-Augmented Generation and its role in enhancing LLM capabilities.
Explore the role of vector databases (Chroma, Milvus) in RAG applications for efficient document storage and retrieval.
Build a working document QA application using LangChain, LlamaIndex, and LLMs.
Build a Text-to-SQL RAG Application
Online
9:00am - 5:00pm ET
Online
9:00am - 5:00pm ET
Online
9:00am - 5:00pm ET
WeCloudData is the leading data science and AI academy. Our blended learning courses have helped thousands of learners and many enterprises make successful leaps in their data journeys.
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