Name: Zero to Hero in LangChain: Build GenAI apps using LangChain
Availability: InStock

What You'll Learn

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

Requirements

Basic Python knowledge, familiarity with AI concepts, and access to a computer with internet are recommended; no advanced AI experience required.

Aspiring AI developers who want to build and deploy advanced Generative AI applications using LangChain
Data scientists aiming to enhance their AI models with memory, retrieval-augmented generation (RAG), and custom tool integrations
Software engineers looking to master LangChain for creating dynamic and interactive AI-driven applications
Tech enthusiasts eager to explore the latest frameworks and techniques for developing cutting-edge AI solutions
AI researchers interested in applying LangChain's features to improve conversational AI and data retrieval systems
Product managers who want to understand the capabilities of LangChain to lead AI-driven product development effectively

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