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
Are you ready to transform your ideas into powerful Generative AI applications? Do you want to master a cutting-edge framework that can revolutionize how you interact with AI models? If you're an aspiring AI developer, data scientist, or tech enthusiast eager to build advanced AI applications from scratch, then this course is designed for you.
"Zero to Hero in LangChain: Build GenAI apps using LangChain" is your comprehensive guide to mastering LangChain, an innovative framework that streamlines the creation of sophisticated AI-driven applications. Whether you're a beginner or someone with some experience in AI, this course will take you on a journey from understanding the basics to implementing complex applications that leverage memory, retrieval-augmented generation (RAG), tools, agents, and more.
In this course, you will:
Develop your first LangChain application and set up a robust development environment.
Master the use of Prompt Templates, Chains, and Runnables to create versatile AI interactions.
Implement dynamic execution flows and output parsing to enhance your AI models.
Harness the power of memory in LangChain to build conversational AI with context retention.
Create a fully functional RAG pipeline to maximize the value of your data retrieval processes.
Build custom tools and agents, and learn how to integrate them into your applications.
Monitor and optimize your applications using LangSmith.
Design user-friendly interfaces for your AI apps with Streamlit.
Why should you learn LangChain? As the AI landscape rapidly evolves, the ability to build applications that can interact intelligently with vast datasets and maintain coherent conversations is a game-changer. LangChain offers a powerful, flexible framework that simplifies this process, making it accessible even if you're just getting started.
Throughout the course, you'll complete hands-on projects that reinforce your learning, ensuring you not only understand the theory but can apply it effectively. From building conversational AI with memory to creating sophisticated RAG applications, you'll gain practical experience in every aspect of LangChain.
This course stands out because it not only covers the "how" but also the "why" behind every feature of LangChain. As an expert in the field, I'll guide you through each step, ensuring you gain the skills and confidence needed to build impactful AI applications.
Don't miss this opportunity to become a LangChain expert and take your AI skills to the next level. Enroll now and start building the future of AI applications!
