AI Agents for Industry

This course is for technically trained professionals in the manufacturing and high-tech industry, such as:

• Operators and first-line production engineers
• Design and test engineers
• Service and quality engineers
• Employees who handle many repetitive questions or tasks

You work daily with machines, processes or technical documentation and want to use AI as a practical tool in your work.

The course is open to professionals with at least an MBO level 4 qualification (HBO level is also suitable), who are employed or have demonstrable work experience. No prior knowledge of AI or programming is required. The needed basics are taught and provided as pre-reading material. So you will get basic knowledge of AI and of programming in Python: on a scale of 0 to 5, around level 2 to 3, so you can run basic Python notebooks.

During the course you work step by step on designing and building an industrial AI solution. It covers, among other things:

• AI in the industrial context: generative AI, GPT models and AI Agents for production, maintenance and quality processes.
• Local GPTs and AI Agents (on-premise): setting up AI that runs locally, with data security, IP protection and compliance.
• Knowledge retrieval with AI (RAG workflows): unlocking manuals, fault logs and maintenance schedules through AI workflows.
• AI workflows for production, maintenance and quality: defining the right point where an AI Agent adds value, so you automate what truly matters.
• Adoption, safety and ethics of AI: responsible, secure use, including the EU AI Act and GDPR.
• From design to practical application: testing, verifying and substantiating your AI solution.

You identify opportunities for AI in production, maintenance and quality processes and translate these into concrete applications. You design and configure a local GPT or AI Agent, unlock existing documentation through AI workflows, and learn to apply AI safely, responsibly and effectively within your organisation.

The course runs for 10 to 12 weeks and follows a blended approach: workshops, tutorials and guided working sessions. You work individually and in small groups on your own case. Through peer learning, feedback and guidance from lecturers, you build a working AI prototype that fits your context. The overall structure:

• Introduction to AI in an industrial context
• Pressure cooker: building a local GPT or AI Agent
• Translating AI concepts to your own work context
• Designing AI workflows for production and maintenance
• In-depth workshops on adoption, ethics and compliance
• Portfolio guidance and completion

You complete the course with a portfolio assessment, showing that you have designed and built an industrial AI application, tested and substantiated its technical functioning, and reflected on its applicability in practice.

The course consists of several half-day sessions and one full-day session:

• Week 0 (from 7 Jan 2027): pre-course preparation, Canvas reading
• Week 1 (14 Jan 2027): Module 1 — Introduction (half-day, 4 contact hrs)
• Week 2 (21 Jan 2027): Module 2 — Pressure Cooker (full day, 8 contact hrs)
• Week 3 (25–29 Jan 2027): Context Analysis & Tool Exploration (self-study, 6 hrs)
• Week 4 (4 Feb 2027): Module 2 — AI in Your Own Work Context (4 contact hrs)
• Week 5 (8–12 Feb 2027): Build Sprint & Design Brief Submission (self-study, 8 hrs)
• Week 6 (18 Feb 2027): Module 3 — AI Workflow & Peer Review (4 contact hrs)
• Week 7 (25 Feb 2027): Module 4 — Workshops & Portfolio Guidance (4 contact hrs)
• Weeks 8–9 (1–12 Mar 2027): Finalisation Sprint (self-study, 10 hrs)
• Week 10 (15–19 Mar 2027): Portfolio Submission Week
• Week 11 (22–26 Mar 2027): Teacher Feedback Period (async)
• Week 12 (Thu 1 Apr 2027): Module 5 — Return Afternoon (4 contact hrs)