Course
Agentic AI Tutorial
A hands-on tutorial for building agentic AI systems in Python — agents that use tools, memory, and reasoning to complete real-world tasks, from a single agent to multi-agent orchestration.
Intermediate
Self-paced
Guide: AI Agents
Overview
A hands-on tutorial for building agentic AI systems in Python — agents that use tools, memory, and reasoning to complete real-world tasks, from a single agent to multi-agent orchestration.
Who this course is for: Python developers and ML engineers who want to build production-minded AI agents.
What you will learn
- How agents plan, use tools, and maintain memory
- Building single-agent and multi-agent workflows
- Connecting agents to external tools and APIs
- Patterns for reliable, observable, production-ready agents
Prerequisites
- Comfortable writing Python
- Basic familiarity with LLMs and REST APIs
Modules
- Agent fundamentals: tools, memory, and reasoning
- Building your first agent end to end
- Multi-agent orchestration and coordination
- Evaluation, observability, and deployment
Resources
- GitHub repository — source code, notebooks, and instructions.
- Related guide: AI Agents
- More structured learning: all courses · the learning hub
- Author: Ruslan Magana Vsevolodovna — Machine Learning Engineer, Data Scientist, Physicist.