Data Engineering Bootcamp
Are you looking to become an expert in data engineering? In this bootcamp, you'll gain expertise in working with Python, Azure, Databricks and PySpark.
- Duration
- 18 weeks (144 hours)
- Time per week
- 8 hours
- Courses
- 6 courses
Who this is for
This fits you if
- Career switchers and professionals who want to become expert data engineers.
Another option may suit you better if
- You have no programming experience at all. Start with Programming with Python Course first.
- You want to analyse and present data rather than move it. Take a look at Data & Analytics Bootcamp instead.
- You do not work with cloud platforms and do not plan to. This bootcamp leans on Azure.
Not sure? Plan a free study advice call
Prerequisites
- Basic computer skills.
What you'll learn
- The basics of data engineering, including Python programming.
- How to build data pipelines in Databricks and manage data in Azure.
- How to apply ethical principles in data engineering.
- How to use your skills effectively in real-world projects and jobs.
The program
Multiple courses of a few weeks each, building on one another.
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1
Data Fundamentals Course
3 weeksBuild your foundation in data: the landscape, the tools and the statistics behind every data role. The starting point for the Data & Analytics, Data Science and Data Engineering bootcamps.
Taught by Patrick Pisani
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2
SQL Foundations Course
3 weeksLearn the fundamentals of SQL for working with structured data. Covers advanced techniques including subqueries, window functions, and CTEs.
Taught by Lucia Riscado Cordas
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3
Fundamentals of a Data Stack Course
3 weeksDo you work extensively with data and want to elevate your skills? Learn to use essential tools that streamline data processing, save time, and enable you to work independently.
Taught by Ali Hurriyetoglu
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4
Azure Data Fundamentals Course
3 weeksWant to build a solid foundation in cloud data management with Microsoft Azure? Learn to work with Azure services for data storage, processing, and analytics.
Taught by Ali Hurriyetoglu
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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
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Final Assignment: Data Engineering
3 weeksThe closing module of the Data Engineering Bootcamp — apply everything you've learned to a real, practical data engineering 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
Lucia Riscado Cordas
Data Visualisation and Storytelling
Lucia runs a data-visualization practice and teaches Microsoft Excel Essentials and SQL, combining analysis with design.
Courses in this bootcamp
Ali Hurriyetoglu
Data Engineering and Data Stack
Ali holds a PhD plus degrees in cognitive science and computer engineering, and teaches data pipeline, data stack, and AI model courses, drawing on academic teaching experience at METU and Radboud University.
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.
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Soonest
2026-10-22
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2026-12-03
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2027-01-14
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2027-02-25
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2027-04-08
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2027-05-20
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.