Build Powerful AI Agents Using smolagents from Hugging Face

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Free Download Build Powerful AI Agents Using smolagents from Hugging Face
Published: 3/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 38m | Size: 286 MB
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.
Who this course is for
AI Enthusiasts & Developers
Data Scientists & Engineers
Finance & Business Professionals
Anyone Curious About AI Agents
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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

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