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Udemy

LangChain in Action: Develop LLM-Powered Applications

via Udemy

Overview

From the Basics of LLMs to Production-Grade Microservice Architecture with Kubernetes (Latest Version 1.0.x)

What you'll learn:
  • Master LangChain from basics to advanced features
  • Understand and implement Retrieval Augmented Generation (RAG) using VectorStores
  • Learn about the creation and use of powerful Autonomous Agents.
  • Grasp the functionalities and applications of the Indexing API.
  • Explore the LangSmith Platform for production ready application
  • Learn about Microservice architecture in the context of large language model (LLM) applications.
  • Learn about the new LangChain Expression Language with the Runnable Interface

This course provides an in-depth exploration into LangChain, a framework pivotal for developing generative AI applications.

Now fully updated for LangChain 1.0.x — including LCEL, LangGraph-based orchestration, the revamped Agents API, and the langchain_classic imports.


Aimed at both beginners and experienced practitioners in the AIworld, the course starts with the fundamentals, such as the basic usage of the OpenAI API, progressively delving into the more intricate aspects of LangChain.

You'll learn about the intricacies of input and output mechanisms in LangChain and how to craft effective prompt templates for OpenAI models. The course takes you through the critical components of LangChain, such as Chains, Callbacks, and Memory, teaching you to create interactive and context-aware AI systems.

Midway, the focus shifts to advanced concepts like Retrieval Augmented Generation (RAG) and the creation of Autonomous Agents, enriching your understanding of intelligent system design. Topics like Hybrid Search, Indexing API, and LangSmith will be covered, highlighting their roles in enhancing the efficiency and functionality of AI applications.

Toward the end, the course integrates theory with practical skills, introducing Microservice Architecture in large language model (LLM) applications and the LangChain Expression Language. This ensures not only a theoretical understanding of the concepts but also their practical applications.

This course is tailored for individuals with a foundational knowledge of Python, aiming to build or enhance their expertise in AI. The structured curriculum ensures a comprehensive grasp of LangChain, from basic concepts to complex applications, preparing you for the future of generative AI.

Syllabus

  • Before we start...
  • Preparation
  • LangChain Basics
  • Chains - From basic to advanced chains
  • Callbacks
  • Memory
  • OpenAI Function Calling
  • Retrieval Augmented Generation (RAG)
  • Agents
  • Indexing API
  • LangSmith
  • Microservice Architecture for LLM Applications
  • LangChain Expression Language (LCEL)
  • Congratulations!

Taught by

Markus Lang

Reviews

4.6 rating at Udemy based on 996 ratings

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