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Designing Agentic Systems with LangChain

IntermediateSkill Level
4.8+
1,717 reviews
Updated 10/2025
Get to grips with the foundational components of LangChain agents and build custom chat agents.
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PythonArtificial Intelligence3 hr11 videos34 Exercises2,800 XP11,091Statement 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

Build intelligent agentic systems! Discover the key components of LangChain agents, including how prompts, LLMs, and tools work together for reasoning and action. You'll set up an agent with OpenAI's API, define custom tools, and tackle real-world tasks like math calculations. Plus, explore how LangChain organizes data using graphs, nodes, and edges.
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2

Building Chatbots with LangGraph

Build dynamic, tool-augmented chatbots with LangChain and LangGraph! You’ll explore how to create a chatbot that adapts based on user input by defining states and integrating external APIs for real-time information retrieval. You'll connect these components into a responsive graph structure, enabling smooth transitions between conversation and tool-assisted responses. By the end, you’ll have a visually represented chatbot framework with enhanced reasoning and multi-step workflows.
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3

Build Dynamic Chat Agents

Expand your chatbot with dynamic tools and memory! Define and integrate multiple tools into flexible workflows, build functions for dynamic tool calling, and configure your chatbot for multiple-tool handling. Organize memory and outputs to enable interleaved, multi-turn conversations. By the end, you'll have created a sophisticated chatbot capable of complex interactions.
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Designing Agentic Systems with LangChain
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*4.8
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  • Nitin
    3 hours ago

    Great content

  • Balaji
    13 hours ago

  • Bhavani
    13 hours ago

  • Hoan
    19 hours ago

  • Madduri
    yesterday

    Good

  • Luong
    2 days ago

"Great content"

Nitin

Balaji

Hoan

FAQs

What is an agentic system?

An agentic system is a smart system that uses AI to complete tasks on its own. It combines tools, workflows, and language models to make decisions and solve problems.

How is this course relevant to my role as a Data Scientist/Data Engineer/AI Engineer?

Each professional role benefits from learning how to automate complex tasks, streamline workflows, and build scalable systems. The course offers tailored insights for enhancing data analysis, pipeline management, and AI automation capabilities.

What outcomes can I expect after completing the course?

By the end of the course, you will be able to build intelligent systems using agentic workflows, configure LangChain agents, integrate tools and APIs, and manage complex workflows to enhance automation, productivity, and problem-solving.

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