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.