Strategic LLMs for Professionals

This course is designed for professionals in managerial, research, or domain specialist roles, including project managers, team leads, department heads, research coordinators, scientist, consultants, and policy professionals, who work in or alongside AI-driven fields and who need to make informed decisions about AI tools. It combines conceptual foundations with hands-on exercises and real-world case studies. Prior knowledge of programming is optional.

The course equips participants with the confidence to evaluate AI tools critically, communicate effectively with technical teams, identify high-value use cases in their domain, and manage AI-related risks. Through guided discussions and applied projects, participants leave with an actionable understanding of where and how LLMs can best serve their organization.

• Foundations of Gen AI and LLMs
• LLM landscape: tools, vendors, and deployment options (cloud vs. on-premises)
• Prompt engineering for professionals
• Identify and evaluate AI use cases in your organization
• LLM workflow, skills, and connectors
• How LLMs are trained and customized in organizations
• Vibe-coding for non-coders (optional)
• Beyond text: multimodal AI with text, Image, video, and sound (optional)
• Building AI assistants
• Building Agentic systems with n8n
• Case studies: document summarization, contract review, literature search, financial reporting, …
• Ethical AI: Bias, fairness, accountability, and responsible deployment

• Understand how LLMs work and what distinguishes different tools
• Identify and evaluate high-impact AI use cases relevant to their own professional domain
• Communicate with technical colleagues and AI vendors confidently when scoping or procuring AI solutions
• Leave with an applied project addressing a real challenge in their own field using LLMs

You can find an overview of our continuing education programmes in the field of computational science and artificial intelligence here.

Lectures, self-study(pre/post), coding exercises, final group/individual project work

By the third session, participants propose a project relevant to their field of interest on which they apply their knowledge of LLMs to solve a problem.  After modification and approval, they have a few weeks to implement and submit their projects.