Introduction to Agentic AI (TTAI2900)

About This Course:

This course introduces the principles and practices of Agentic AI, a form of intelligent systems that moves beyond the limits of chat-based AI or productivity assistants. While familiar tools like ChatGPT or Microsoft Office’s Copilot respond to user prompts in the moment, Agentic AI systems are designed to act more autonomously. They can plan steps toward a goal, use tools and data, remember past interactions, and continue working even when not being directly prompted.

Across two days, the course introduces the foundations of agent-based systems, showing how they differ from predictive or reactive AI approaches. It explains the core architectures that drive agent behavior, including cycles of perception, planning, action, and reflection, and highlights how prompts and memory shape their decision-making. We will also looks at more advanced setups, such as groups of agents working together, and connects these ideas to real-world applications like research automation, customer support, and business workflows.

Course Objectives:

• Explain what Agentic AI is and how it differs from traditional, predictive, and chat-based AI.

• Describe the core architectures and memory systems that drive agent behavior.

• Recognize how prompts and goal-setting influence agent planning and decision-making.

• Understand how agents make choices, adapt through feedback, and handle uncertainty.

• Identify the features of multi-agent systems and how agents coordinate with each other.

• Relate Agentic AI concepts to real-world application.

• Discuss ethical risks and apply responsible design principles for safe deployment.

Audience:

• This course is designed for business leaders, product managers, consultants, and operations professionals who want to understand how Agentic AI can be applied in practice. The course is intended for non-developers who need to evaluate AI opportunities, guide adoption, or work effectively with technical teams on agent-based systems.

Prerequisites:

• Participants are expected to have a basic understanding of artificial intelligence. Prior exposure to large language model–based tools like ChatGPT or Microsoft Copilot is also necessary, as the course builds directly on those concepts. While no programming or coding experience is required, learners should be comfortable with general technology concepts and able to follow discussions about how AI systems are structured and applied.