The AI Agent Development Fundamentals course is designed for developers, engineers, and technical product builders who are new to Generative AI but already have intermediate machine learning knowledge, basic Python proficiency, and familiarity with development environments such as VS Code, and who want to engineer, customize, and deploy open generative AI solutions while avoiding vendor lock-in.

The course introduces learners to the core design patterns and practical skills required to build autonomous AI agents. Learners begin by studying the architectural foundations of agent systems, including perception, reasoning, and action loops, as well as the differences between reactive, deliberative, and hybrid agent types. The course then focuses on building simple reactive agents, where learners apply structured prompting, decision-making frameworks, and natural language understanding to implement predictable and testable behaviors. In the final module, learners extend their agents with tool-use and memory management capabilities, using function-calling patterns, conversation history maintenance, and context window optimization. Practical exercises emphasize building agents with resilience through error handling and recovery strategies. By the end of the course, learners will have created functional agents capable of integrating tools, maintaining memory, and performing autonomous tasks.