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    Build Powerful Ai Agents Using Smolagents From Hugging Face

    Posted By: ELK1nG
    Build Powerful Ai Agents Using Smolagents From Hugging Face

    Build Powerful Ai Agents Using Smolagents From Hugging Face
    Published 3/2025
    MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
    Language: English | Size: 170.92 MB | Duration: 0h 38m

    Learn to create autonomous AI agents using Smolagents, integrating tool-calling, LLMs, and real-world applications.

    What you'll learn

    Understand AI Agents & Multi-Agent Systems

    Build AI Agents Using the Smolagents Library

    Develop Custom AI Agents for Real-World Applications

    Integrate AI Agents with External APIs & Tools

    Requirements

    Basic Python programming skills

    Familiarity with AI concepts

    Internet access

    Description

    AI agents are transforming the way we work. Sam Altman predicts that AI coworkers will enter the workforce in 2025, and companies like OpenAI, xAI, and DeepMind are already launching cutting-edge AI agents like Operator and DeepSearch.But how do you build your own AI agent? Which framework should you use?If you like graph-based control, LangGraph is an option.If you prefer role-based AI teams, CrewAI works well.If you're into prompt optimization, DSPy can be adapted.However, if you want a lightweight, flexible, and straightforward way to build AI agents, Smolagents from Hugging Face is the answer.Why Choose Smolagents?No unnecessary abstractions—simple yet powerful.Access any LLM in the world—OpenAI, Together AI, OpenRouter, Mistral, or even your own models.Create custom tool-calling agents that can interact with real-world data, APIs, and more.What You’ll Learn in This Course:The fundamentals of AI agents—how they work and why they matter.Building a tool-calling agent—connecting your agent to external tools and APIs.Integrating AI models like GPT-4, Gemini, and Claude—leveraging multiple AI brains.Creating custom AI tools—fetch financial data, analyze documents, or search the web.Multi-agent systems—designing AI agents that collaborate.Building a text-to-SQL agent for querying databases.Creating a financial analyst AI to automate investment research.Whether you're a developer, researcher, or AI enthusiast, this course will equip you with the skills to build, deploy, and scale AI agents for real-world use cases. Start learning today.

    Overview

    Section 1: Introduction to the Art and Science of Building AI Agents

    Lecture 1 What is an AI Agent?

    Lecture 2 Why Choose smolagents

    Lecture 3 Build a Code AI Agent

    Lecture 4 Build a Tool-Calling AI Agent (Step 1)

    Lecture 5 Taste of OpenRouter

    Lecture 6 Build a Tool-Calling AI Agent (Step 2)

    Section 2: Multi-Agent Systems

    Lecture 7 Building a Multi-Agent System (1)

    Lecture 8 Building a Multi-Agent System (2)

    Lecture 9 Building a Multi-Agent System (3)

    Section 3: Applications

    Lecture 10 Build an AI Financial Analyst

    Lecture 11 Build a Text-to-SQL Agent

    AI Enthusiasts & Developers,Data Scientists & Engineers,Finance & Business Professionals,Anyone Curious About AI Agents