Learn Generative AI and Large Language Models

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Tutorial Overview

LangChain Agents

The "LangChain Agents" workshop delves into the "Agents" component of the LangChain library, offering a deeper understanding of how LangChain integrates Large Language Models (LLMs) with external systems and tools to execute actions. This workshop builds on the concept of "chains," which can link multiple LLMs to tackle various tasks like classification, text generation, code generation, and more. "Agents" enable LLMs to interact with external systems and tools, making informed decisions based on available options. 

The workshop explores the different types of agents, such as "Zero-shot ReAct," "Structured input ReAct," "OpenAI Functions," "Conversational," "Self ask with search," "ReAct document store," and "Plan-and-execute agents." It provides practical code examples, including initializing LLMs, defining tools, and creating agents, and demonstrates how these agents can answer questions using external APIs, offering participants a comprehensive overview of LangChain's agent capabilities.

Tutorial Topics:

  • Agents
  • Concept of Chains
  • LangChain Agents
  • Types of Agents
  • Plan and Execute Agents


 

Meet your instructor

Senior Machine Learning Engineer / Data Science Consultant

Mary Grace Moesta

Mary Grace Moesta is a senior data science consultant at Databricks. She's been working in the big data and data science space for several years with opportunities to collaborate across several verticals, with the majority of her work focused in the Retail and CPG space. Prior to Databricks, Mary Grace was able to contribute to several machine learning applications, namely - personalization use cases, forecasting, recommendation engines, and customer experience measures.

Course Curriculum

  • 1

    Welcome to the Tutorial!

    • Welcome to the tutorial!

    • What You'll Learn in This Tutorial

    • How to use this tutorial

    • Tutorial Prerequisites

  • 2

    LangChain Agents

    • LangChain Agents

    • Agents quiz

    • Lesson Notebook: LangChain Agents

CODE TO LEARN

A Hands-on Tutorial

This hands-on tutorial goes beyond the basics, offering you an interactive Coding Notebook crucial to your educational journey. It immerses you in an engaging process of writing, generating, and executing code, enabling a comprehensive exploration of the tutorial's core concepts through practical coding exercises. By applying these concepts in real time, you'll witness the immediate impact of your coding choices. This hands-on approach is not just about learning to code; it's about coding to learn, solidifying your understanding as you seamlessly generate and execute code.

Enroll now!

Accelerate your journey to enerative AI by enrolling in our program today!