Learn the fundamentals of building autonomous AI agents that can tackle multi-step tasks without constant human direction. This beginner-friendly course guides you through the core concepts of agentic AI, including task planning, tool use, and iterative problem-solving. You'll discover how modern large language models can be orchestrated to reason about complex workflows and execute actions intelligently. By the end of this tutorial, you'll have built a practical AI agent capable of researching topics, synthesising information, and taking autonomous actions. We'll explore real-world examples, common patterns, and best practices for agent design. Whether you're interested in automation, AI workflows, or understanding the future of AI applications, this course provides the essential knowledge to get started. No advanced programming experience required—just curiosity and a willingness to learn how to work with cutting-edge AI technology.

Lessons

  1. What Are Autonomous AI Agents? — Understanding agentic AI, autonomy levels, and real-world applications (+50 XP)
  2. Agent Architecture and Core Components — Exploring the building blocks: reasoning engine, memory, tools, and planning (+75 XP)
  3. Designing Tasks and Planning Workflows — Teaching agents to break down complex goals and create action plans (+75 XP)
  4. Implementing Tool Use and Actions — Building function calling systems and giving agents the ability to act (+100 XP)
  5. Building Your First Research Agent — Hands-on: Creating a complete autonomous agent from scratch (+125 XP)
  6. Debugging, Iteration, and Best Practices — Optimising agent behaviour, handling failures, and production considerations (+75 XP)