See your options for further education in Artificial intelligence
Getting started with Agentic AI: From Business Use Cases to Working Agents
For professionals ready to move from using AI tools to understanding, designing and testing agentic AI workflows.
Agentic AI opens new possibilities for professionals who want to move beyond one-off prompting and explore how AI can support more complex tasks and workflows. But working effectively with agents requires more than access to powerful tools. It requires an understanding of how agents reason, plan, use memory and tools, and respond to the data, context and instructions they are given.
This two-day course introduces you to the fundamentals of agentic AI systems and gives you a practical foundation for designing, testing and improving simple agents. Through hands-on exercises, you will work with real-world tasks, translate them into structured workflows, apply common design patterns and learn how to anticipate the limitations, risks and failure modes that affect agent performance.
Learning outcomes of »Getting started with Agentic AI«
Course directors on »Getting started with Agentic AI«
Course details for »Getting started with Agentic AI«
Schedule and delivery
Dates
Thursday, 8 October 2026
Friday, 9 October 2026
Workload
The total number of hours for this course is 16 hours including teaching and exercises.
Day 1: Foundations of AI Agents
Day 1 introduces the core concepts behind agentic AI systems and quickly moves into practical application. You’ll learn how agents use reasoning, memory, and tools to solve tasks, and how design patterns structure their behavior. These concepts are applied in hands-on exercises using no-code tools.
By the end of the day, you will be able to:
- Understand the core components of agentic AI systems
- Apply basic design patterns to structure agent behavior
- Translate real-world tasks into step-by-step agent workflows
- Build and test a simple AI agent using no-code tools
Day 2: Data, Limitations, and Building Reliable Agents
Day 2 focuses on foundations that make agents work in practice: well-structured data, robust design, and awareness of limitations. You’ll learn how the quality and structure of inputs, such as prompts, context, and documents, directly impact performance. The day also covers common failure modes, risks, and practical techniques to make agents more reliable, predictable, and safe. Through hands-on exercises, you will refine and improve your agents.
By the end of the day, you will be able to:
- Structure and prepare input data (prompts, context, documents) for agents
- Diagnose common failure modes in agent behavior
- Improve reliability through better prompting, memory use, and iteration
- Apply practical safeguards to reduce errors and unintended outputs
- Build more robust agents that perform consistently on real tasks
Target audience
This course is designed for professionals who want a practical introduction to agentic AI beyond theory.
During the course we use accessible no-code/low-code tools for prototyping, but the skills are platform-agnostic. You will learn transferable concepts that can later be applied in whichever AI ecosystem your company prefers.
No prior experience with AI agents is required.
Fee
10,000 DKK
Location
Faculty of Science
Department of Computer Science
Universitetsparken 5
DK-2100 Copenhagen Ø
