Zero to Hero in LangChain: Build GenAI apps using LangChain

Post published:17 September, 2025
Post category:StudyBullet-20
Reading time:4 mins read

Learn all features of LangChain & build Generative AI applications with Memory, RAG, Tools, Agents etc. using LangChain

What you will 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

Add-On Information:

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Architecting Intelligent Systems: Learn to design and assemble sophisticated Generative AI applications from the ground up, moving beyond simple API calls to structured, modular, and scalable solutions for real-world problems.
Crafting Dynamic Conversations: Master the art of guiding Large Language Models (LLMs) to produce precise, contextually rich, and human-like responses, enabling engaging and effective interactions across diverse conversational scenarios.
Building Cohesive AI Logic: Understand how to sequence and link different AI operations seamlessly, creating multi-step processes and sophisticated workflows that significantly enhance application intelligence and capabilities.
Implementing Adaptive Execution Paths: Gain the expertise to build intelligent workflows that can dynamically choose the best course of action based on real-time inputs and evolving conditions, making your applications highly flexible, robust, and responsive.
Endowing AI with Long-Term Recall: Develop advanced techniques to equip your AI applications with the ability to maintain conversational context, remember past interactions, and personalize user experiences across multiple sessions.
Empowering AI with External Knowledge: Discover how to effectively augment LLMs with up-to-date, factual information from various external sources, effectively overcoming inherent knowledge limitations and significantly reducing AI hallucinations.
Extending AI’s Reach with Custom Functionality: Acquire the skills to integrate specialized tools, external APIs, and even custom logic, transforming your AI from a passive responder into an active problem-solver capable of performing real-world tasks.
Orchestrating Complex AI Behaviors: Learn to choreograph multiple AI components – from powerful language models to specific actions and extensive knowledge bases – into coherent, goal-oriented applications that exhibit advanced reasoning and autonomous capabilities.
Making AI Accessible and Interactive: Master the deployment of your sophisticated Generative AI applications with intuitive graphical interfaces using Streamlit, ensuring a user-friendly and engaging experience for your end-users.
Unlocking Full GenAI Potential: This course equips you with the comprehensive framework and practical skills to transform theoretical GenAI concepts into tangible, deployable applications that address complex real-world challenges across various industries.
Developing for the AI Frontier: Position yourself at the forefront of AI innovation by mastering LangChain, the definitive industry-standard toolkit for building and scaling cutting-edge LLM-powered applications.
Solving Real-World Use Cases: Apply LangChain’s powerful abstractions to tackle practical business problems, from intelligent chatbots and advanced content generation to sophisticated data analysis assistants and automated workflows.

Pros:

Rapidly prototype and deploy complex Generative AI solutions with a structured and efficient framework.
Gain a highly sought-after and immediately applicable skill set in the rapidly evolving AI job market.
Demystify the process of building production-ready LLM applications, moving beyond basic tutorials.
Learn from practical, hands-on examples that solidify understanding and encourage creative application.
Become proficient in a versatile framework that simplifies advanced AI concepts and component orchestration.