Applied AI Bootcamp
Learn to apply AI in practice with hands-on experience in prompt engineering, AI agents, LangChain, RAG, and AI ethics.
- Duration
- 18 weeks (144 hours)
- Time per week
- 8 hours
- Courses
- 6 courses
Who this is for
This fits you if
- Professionals who want to apply AI practically in their work — from prompt engineering to building AI agents.
Another option may suit you better if
- You have never used generative AI at work. Start with AI Essentials Bootcamp first.
- You want to work in a Python codebase and deploy models. Take a look at AI Engineering Bootcamp instead.
- You mainly need to steer AI adoption in your organisation. Take a look at AI Professional Bootcamp instead.
Not sure? Plan a free study advice call
Prerequisites
- No prior AI experience required.
What you'll learn
- Learn how to craft effective prompts and automate complex tasks using large language models.
- Build AI agents that connect to tools, APIs, and data sources using n8n.
- Understand how to design AI-powered workflows that reason, retrieve, and act autonomously.
- Develop a practical AI strategy aligned with business goals, including risk management and adoption planning.
The program
Multiple courses of a few weeks each, building on one another.
-
1
AI Fundamentals Course
3 weeksThe foundation course for every AI professional. Understand what AI is, how large language models work, and how to apply generative AI in your own field.
Taught by Patrick Pisani
-
2
Vibe Coding with Lovable Course
3 weeksThe way we build software has fundamentally changed. In this hands-on course you'll learn to describe what you want to build and let AI do the heavy lifting — no coding background required.
Taught by Marta Strykowska
-
3
Building AI Agents Course
3 weeksBuild your own AI agents, no coding needed. Learn to design agents that perceive, reason, act, and remember, then build and automate them with no-code tools like n8n and Claude.
Taught by Marek Durcek
-
4
Retrieval-Augmented Generation (RAG) Course
3 weeksLearn RAG, a cutting-edge technique that enhances LLMs with external knowledge. Combine vector databases with LLMs to build accurate, grounded AI applications.
Taught by Akos Steger
-
5
AI Literacy & Ethics Course
3 weeksExplore the ethical, legal, and social implications of AI including the EU AI Act. Learn to evaluate and design responsible AI strategies.
Taught by Hanan ElNaghy
-
Final Assignment: Applied AI
3 weeksThe closing module of the Applied AI Bootcamp — apply everything you've learned to a real, practical AI project.
Taught by Sabine Joseph
What a week looks like
Every course in this bootcamp runs for 3 weeks, and every week looks like this.
8 hours per week
5 hours
Self-study
Course material and exercises on our learning platform, whenever suits you.
1 hour
Live with your teacher
A fixed moment every week, online or at Science Park. Small group, so you get to participate.
2 hours
On your own work
Do the assignment on your own data and your own situation. No exercise files.
Teachers for this bootcamp
Patrick Pisani
Data Analytics and Business Intelligence
Patrick is a data analyst with experience across finance, tech, and government, including forecasting models at Just Eat Takeaway.com. He teaches data and AI fundamentals courses.
Courses in this bootcamp
Marta Strykowska
Vibe Coding and AI Native Apps
Marta has over a decade building digital products and now focuses on AI-native app development. She teaches Vibe Coding.
Courses in this bootcamp
Marek Durcek
AI Agents for Marketing and Sales
Marek is an AI and automation consultant who designs practical automations around existing workflows, and teaches Building AI Agents.
Courses in this bootcamp
Akos Steger
RAG, Language Technology, Deep Learning
Akos trained originally as a linguist before moving into AI and language technology, and now teaches machine learning, RAG, deep learning, and language-technology courses.
Courses in this bootcamp
Hanan ElNaghy
AI Literacy, Machine Learning, Python
Hanan holds a PhD in computer vision and is an Assistant Professor in Cairo alongside her work here. She teaches AI literacy and ethics, machine learning, Python, and prompt engineering.
Courses in this bootcamp
Sabine Joseph
Machine Learning and Data Science
Sabine holds a PhD in cognitive neuroscience from UCL and has worked at Microsoft, Accenture, and Reed building machine learning and recommender systems.
First live sessions
These are the dates of each group's first live session with the teacher. You don't have to wait for them: as soon as you register, you get access to the learning materials and can start with the self-study.
-
Soonest
2026-10-20
-
2026-12-01
-
2027-01-12
-
2027-02-23
-
2027-04-06
-
2027-05-18
None of these dates work for you? Let us know and we'll think along with you.
Choose your format
The content, the teacher and the certificate are the same in all three formats. What differs is the focus and the planning, and that's reflected in the price.
With your team
Most affordable per person from four participants.
- From four participants
- Built around your own cases
- On location or remote
- Subsidy often possible
In a group
The usual way: you share the teacher with a few others and follow a fixed schedule.
- Fixed start date, fixed schedule
- Small group of fellow students
- Shared teacher
Individual
For anyone who prefers to work at their own pace.
- Start whenever you want
- Your own pace and planning
- Teacher just for you
- Personal guidance
Flexible payment
Payment options
Through your employer, with a voucher or in instalments: there's usually a way that works. Not sure which fits you? We're happy to think it through with you, free and without obligation.
Option 1
Through your employer
We can invoice your employer directly, with 30 days to pay. If it helps, we'll give you a training plan to discuss internally.
Option 2
With a government contribution
A UWV training voucher or a municipal voucher can cover (part of) the cost. We're on the approved lists, CRKBO-registered, and glad to help with the application.
Training with colleagues? Your employer may be able to use the SLIM subsidy; we're happy to do the application together.
Option 3
Paying yourself
Pay the full amount at once, or spread it: 3 or 5 instalments at no extra cost, or an interest-free loan through TechMeUp. You choose when you register.