Course Description

Introduction to LangChain for Agentic AI is a hands-on course designed to introduce you to the LangChain framework, empowering you to build advanced AI applications. You'll learn how to integrate large language models (LLMs) with external data sources, create custom prompt chains, and design AI agents. The course covers key concepts such as state management, API integration, and managing complex AI workflows. Perfect for beginners and AI enthusiasts, this course equips you with the essential skills to start building scalable, intelligent applications using LangChain.

Course curriculum

  • 1
    Intro to the LangChain Ecosystem
    • Course Introduction
    • Introduction to LangChain
    • Course Handouts (updated on 2024-12-18)
    • Introduction to LangGraph
    • How to Use Commercial LLMs
    • How to Use Open-Source LLMs
    • Quiz
    • Reading Resources
  • 2
    LangChain Expression Language (LCEL) Essentials
    • LangChain Expression Language (LCEL)
    • Hands On - LangChain Expression Language (LCEL)
    • Future Outlook of LangChain
    • Quiz
    • Reading Resources
  • 3
    Managing LLM Input / Output with LangChain
    • Introduction to LLM Input, Output
    • LLMs and Chat Models
    • Hands-On LLMs and Chat Models (Part I)
    • Hands-On LLMs and Chat Models (Part II)
    • Hands-On LLMs and Chat Models (Part III)
    • Prompting with Prompt Templates
    • Hands-On Prompting with Prompt Templates (Part I)
    • Hands-On Prompting with Prompt Templates (Part 2)
    • Output Parsers
    • Hands-On Output Parsers
    • LLM Advanced Operations
    • Hands-On LLM Advanced Operations
    • Quiz
    • Reading Resources
  • 4
    Project: Prompt Engineering with LangChain and ChatGPT
    • Project - Prompt Engineering with LangChain and ChatGPT - Part I (Introduction)
    • Project - Prompt Engineering with LangChain and ChatGPT - Part II (Review Analyst)
    • Project - Prompt Engineering with LangChain and ChatGPT - Part III (Research Paper Analyst)
    • Project - Prompt Engineering with LangChain and ChatGPT - Part IV (Social Media Marketing Analyst)
    • Project - Prompt Engineering with LangChain and ChatGPT - Part V (IT Support Analyst)
    • Quiz
  • 5
    Building LLM Chains and Conversational Applications with LangChain
    • Recap of Legacy and LCEL Chains
    • Hands-On LLM Chains with LCEL
    • Hands-On Conversation Chains and Memory with LCEL - Part I
    • Hands-On Conversation Chains and Memory with LCEL - Part II
    • Hands-On Conversation Chains and Memory with LCEL - Part III
    • Quiz
    • Reading Resources
  • 6
    Project: Advanced LLM Chains with LangChain
    • Mini-Project: Building a Customer Support Agent
    • Mini-Project: Building a Report Generator
    • Mini Project: Building a Customer Review Analyst
    • Project: Build a Multi-user Conversational Product Recommendation Agent - I
    • Project: Build a Multi-user Conversational Product Recommendation Agent - II
    • Quiz
    • Project: Study Assistant for Quiz Question Generation
    • Course Conclusion

Who Should Enroll?

  • AI Enthusiasts looking to expand their knowledge in building intelligent applications.

  • Developers and Engineers who want to integrate large language models with real-world data.

  • Text length of individual points can be shorter or longer depending on your needs

Key Takeaways

  • Learn to Build AI Workflows by integrating large language models with external data sources using LangChain.

  • Master Prompt Chaining and design custom AI agents to perform complex tasks and automate workflows.

  • Text length of individual points can be shorter or longer depending on your needs

About the Instructor

Dipanjan Sarkar - Head of Community and Principal AI Scientist, Analytics Vidhya

Dipanjan Sarkar is a distinguished Lead Data Scientist, Published Author, and Consultant, having a decade of extensive expertise in Machine Learning, Deep Learning, Generative AI, Computer Vision, and Natural Language Processing. His leadership spans Fortune 100 enterprises to startups, crafting end-to-end data products and pioneering Generative AI upskilling programs. A seasoned mentor, Dipanjan advises a diverse clientele, from novices to C-suite executives and PhDs, across Advanced Analytics, Product Development, and Artificial Intelligence. His recognitions include "Top 10 Data Scientists in India, 2020," "40 under 40 Data Scientists, 2021," "Google Developer Expert in Machine Learning, 2019," and "Top 50 AI Thought Leaders, Global AI Hub, 2022," alongside global accolades and a Google Champion Innovator title in Cloud AI/ML, 2022.
About the Instructor

FAQ

  • Q. What is LangChain and why should I learn it?

    LangChain is a framework for building AI applications by integrating large language models (LLMs) with external data and APIs. Learning it helps you create intelligent workflows and custom AI agents for real-world use.

  • Q. Do I need prior experience with AI or programming to enroll?

    A. No prior AI or LangChain experience is required. Basic programming knowledge, especially in Python, is helpful but not essential, as the course covers everything from scratch.

  • Q. What practical skills will I gain from this course?

    A. You'll learn to build AI applications, integrate LLMs with external data, design prompt chains, and create AI agents with LangChain, along with hands-on state management and API integration.

  • Q. Is this course suitable for professionals already working with AI?

    A. Yes, the course is great for professionals who want to expand their AI skills by learning how to integrate LLMs into workflows and build custom AI agents.

  • Q. How will this course help me apply LangChain in real-world projects?

    A. You’ll gain practical experience building real-world AI applications, learning how to use LangChain to create scalable, intelligent solutions ready for deployment.