AI agents can sound like a buzzword. But the ideas behind them are clear and useful. You can use them to change data, write content, support users, and run research tasks. When you learn how they work, you can build tools that fit your real needs.
This course shows you how to build these tools step by step. You learn how AI agents and AI workflows work, where they differ, and when to use each one. You also see how models, code, and data fit together to form a full AI system.
What You Learn
You get clear rules, simple theory, and code that you can test at once. You start with the core ideas behind agents and workflows. Then you move to real cases that show how these ideas work in practice.
- Plain and structured guides on AI workflows and agents
- Many practical examples like content tools, support bots, and research helpers
- Concepts that work in any programming language
Skills You Build
You will build agents and workflows from scratch. You will use the OpenAI API in Python, and learn patterns you can reuse in other languages.
- Create AI workflows and agent systems
- Work with OpenAI models through API and SDK
- Change and prepare input data with AI
- Build AI‑based automations
- Connect your systems to services like Slack
- Use AI for self-check and result review
- Manage short and long-term memory for agents
- Build multi-agent systems and share data between them
- Split work between general and focused agents
- Add Human‑in‑the‑Loop steps to improve quality
All examples use Python with the OpenAI API and SDK. The ideas stay the same in other languages, so you can apply them to your own stack.
