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AI Agents with Hugging Face smolagents

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3 hr
2,300 XP
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Course Description

AI agents are changing how we work with data and software. From automating workflows to helping users navigate complex tasks, agents can search, reason, and act on your behalf. In this course, you’ll learn how to build agents using smolagents, a lightweight Python framework developed by Hugging Face.Get Hands-On With Code Agents and ToolsYou’ll start by understanding what makes code agents different and why they're so powerful. Then, you’ll build your first agent from scratch, using smolagents to generate and execute Python code. You’ll also learn how to plug in built-in tools and create custom tools to extend what your agents can do.Make Agents Smarter With RAG and MemoryNext, you’ll use retrieval-augmented generation (RAG) to help agents pull info from large document collections. You’ll take things further by building agentic RAG systems—agents that reason over multiple steps to get better answers. You’ll also learn how to add memory so agents can handle follow-up questions naturally and keep track of what’s already been done.Coordinate Multi-Agent Systems and Validate OutputsIn the final chapter, you’ll build multi-agent systems that coordinate specialist agents through a manager. You’ll add planning intervals, use callbacks for insight into agent behavior, and validate final answers, so your agents stay reliable and user-friendly.By the end of the course, you’ll know how to build agents that think ahead, work together, and get things done.
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  1. 1

    Introduction to Hugging Face smolagents

    Free

    Discover what makes code agents special and how they use Python to reason and act. Build your first agent with smolagents, add built-in and community tools for web access, and create custom tools to connect agents with data.

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    Introduction to Hugging Face smolagents
    50 xp
    Let the Agent Do the Math: Expense Insights
    100 xp
    Wait, You Didn't Write Any Functions?
    50 xp
    Creating an Agent With Tools
    50 xp
    Writing Code Through Prompts: Compound Interest
    100 xp
    Let Agents Search the Web
    100 xp
    Creating an Agent With Custom Tools
    50 xp
    Just Add @tool: Writing a Custom Tool
    100 xp
    Check, Please! Giving Agents Access to Data
    100 xp
    One Prompt, Many Tools
    100 xp
  2. 2

    Agentic RAG and Multi-Step Agents

    Transform your traditional RAG pipeline into an agentic system that retrieves information iteratively and reasons across multiple steps. Build stateful tools to support advanced retrieval, guide agents with planning intervals to improve outcomes, and use callbacks to track and customize agent behavior at runtime.

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  3. 3

    Multi-Agent Systems, Memory and Validation

    Tackle complex workflows by orchestrating teams of specialized agents under a coordinating manager. Add memory to retain context across interactions, debug agent behavior using execution traces and reasoning steps, and implement robust validation strategies to ensure high-quality, reliable responses.

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Training 2 or more people?

Get your team access to the full DataCamp platform, including all the features.

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collaborators

Collaborator's avatar
Bex Tuychiyev
Collaborator's avatar
Thalia Barrera
Adel Nehme HeadshotAdel Nehme

VP of Content, DataCamp

Adel is a Data Science educator, speaker, and Evangelist at DataCamp, where he has released various courses and live training on data analysis, machine learning, and data engineering. He is passionate about spreading data skills and data literacy throughout organizations and the intersection of technology and society. He has an MSc in Data Science and Business Analytics. In his free time, you can find him hanging out with his cat Louis.
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