Building Smarter Real-World Generative AI Systems

Building Smarter Real-World Generative AI Systems with LangGraph and LangChain

Welcome to Building a Generative AI Application with LangGraph by Learner’s Spot! This course is designed to equip you with the knowledge and skills needed to create your very own Generative AI application. Whether you’re a beginner or looking to deepen your understanding, we’ve structured this course to guide you step-by-step through essential concepts and practical applications.

What you’ll learn

  • Explore Lang graph and Build Agentic Applications.
  • Learn Generative AI using Langchain and Lang Graph.
  • Explore Lang graph and Build Agentic Applications.
  • Provides End to end tutorial for LangChain.

Course Content

  • Introduction –> 1 lecture • 3min.
  • Generative AI & LLMs: A Comprehensive Guide –> 2 lectures • 5min.
  • Introduction to LangChain –> 2 lectures • 5min.
  • Setting Up Environment –> 5 lectures • 11min.
  • Tools and Agents –> 10 lectures • 10min.
  • Introduction to LangGraph –> 8 lectures • 8min.
  • LangGraph Key Terminologies –> 7 lectures • 22min.
  • Smart Chatbot with LLM and Tavily Web Search – First Graph Application –> 3 lectures • 16min.
  • Introducing RAG World –> 3 lectures • 10min.
  • Building an Intelligent QA App for Web Data with Vector DB in LangGraph –> 8 lectures • 18min.
  • Conclusion –> 1 lecture • 1min.

Building Smarter Real-World Generative AI Systems

Requirements

Welcome to Building a Generative AI Application with LangGraph by Learner’s Spot! This course is designed to equip you with the knowledge and skills needed to create your very own Generative AI application. Whether you’re a beginner or looking to deepen your understanding, we’ve structured this course to guide you step-by-step through essential concepts and practical applications.

What You’ll Learn:

  1. Introduction to Generative AI & LLMs: Kick off your journey with a comprehensive overview of Generative AI and Large Language Models. Understand the fundamental principles behind these technologies and how they empower intelligent applications.
  2. Exploring the Langchain Framework: Dive into the components of the Langchain Framework and discover how data flows within it. We’ll prepare you for hands-on work by setting up your development environment with Python and Langchain.
  3. Utilizing Langchain’s Tools: Learn how to leverage Langchain’s built-in tools and how to create custom ones tailored to your unique needs.
  4. Understanding Agents: We’ll introduce you to the concept of Agents, with a special focus on the REACT agent, discussing its advantages and limitations.
  5. Deep Dive into LangGraph: The heart of this course is LangGraph. Explore its key features, advanced functionalities like the multi-agent approach, and smart planning through real-world examples.
  6. Mastering Key Terminologies: Get familiar with essential LangGraph terminologies, such as states, nodes, and edges, and understand their significance in building structured AI systems.
  7. Building Your First AI-Driven Chatbot: Apply what you’ve learned by constructing your first chatbot using LangGraph. This hands-on project will provide practical experience with the framework.
  8. Exploring Retrieval-Augmented Generation Applications: Discover how Retrieval-Augmented Generation (RAG) applications enhance language models by integrating external information retrieval before response generation.
  9. Hands-On RAG Application Session: Participate in a guided session to create a RAG application, solidifying your understanding of this powerful approach.
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