Learn all features of LangChain & build Generative AI applications with Memory, RAG, Tools, Agents etc. using LangChain
What you will learn
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Discover the core principles of LangChain and its application in building Generative AI models
Master the creation and use of Prompt Templates, including chat prompt templates and few-shot prompt templates, to optimize AI interactions
Develop complex chain structures, such as LLMChains and Sequential Chains, to enhance the functionality of AI-driven applications
Implement dynamic execution flows using LCEL-based Chains and Runnables, including controlling execution flow and dynamic routing
Utilize memory in LangChain to build advanced conversational AI that can remember and recall user interactions across sessions
Create a Retrieval-Augmented Generation (RAG) application, including document reading, chunking, embedding, and data retrieval from a vector database
Design and integrate custom tools and agents, including memory-enabled agents, into your LangChain applications to extend their capabilities
Construct a graphical user interface (GUI) for your Generative AI applications using Streamlit, enabling user-friendly interactions with your AI models
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