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Designing Agentic Systems with LangChain

Intermediate
Updated 01/2025
Get to grips with the foundational components of LangChain agents and build custom chat agents
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PythonArtificial Intelligence3 hours11 videos34 exercises2,800 XPStatement of Accomplishment

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Course Description

Agentic workflows that integrate LLMs and tools to perform nuanced tasks are at the forefront of the AI transformation. In this course, you'll learn the key principles behind LangChain agents, including configuring prompts, integrating tools, and managing complex workflows. By the end of this course, you'll be able to build intelligent systems that automate complex tasks, enhance productivity, and provide dynamic solutions tailored to specific business needs.

Master the Essentials of LangChain Agents

You'll learn how to integrate prompts, language models, and tools into workflows using the Reasoning and Action (ReAct) framework. Following that, you'll be able to set up agentic workflows, configure tools, and understand the core principles of LangChain agents while visualizing these workflows with LangGraph. You'll build custom agents, set up tools for accessing external data sources like the Wikipedia API, and manage agent states. You'll be guided through defining nodes and edges, creating conditional pathways, and assembling complex workflows that adapt to varying conditions.

Build Dynamic Chat Agents

Finally, you'll learn to monitor messages, define nodes for flexible function calling, and configure your chatbot for multiple-tool handling. By the end of this course, you'll be able to build intelligent systems that automate complex tasks, enhance productivity, and provide dynamic solutions tailored to specific business needs.

Prerequisites

Developing LLM Applications with LangChain
1

The Essentials of LangChain agents

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2

Building Chatbots with LangGraph

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3

Build Dynamic Chat Agents

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Designing Agentic Systems with LangChain
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