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Applied Data Science

Machine learning is used in online shops, in online banking security and in social media. Deep learning generates subtitles for You Tube videos and provides speech recognition on phones and facial recognition for photos. In the Applied Data Science minor, you will explore the possibilities of machine learning and deep learning. You will be able to immediately put into practice the knowledge you gain.

For deep learning, you will battle on Kaggle, the online platform for data scientists. You will participate in two real competitions: one on handwriting recognition and one on image classification. Furthermore, you will contribute to a current project of the Data Science lectorate. Organisations from the region engage this lectorate for questions and challenges where data science can provide an answer or solution. For example, deep learning and machine learning techniques can be used to calculate the passing time of vessels at a lock, predict the loss of power when a wind turbine must be shut down in high winds for safety reasons, or determine the maximum vibration load caused by (freight) traffic on the Zeeland Bridge. In the project, you work with fellow students and with researchers from the lectorate. You will keep your client informed of the project progress. Your work on data during this minor will definitely make a contribution to essential research.

Two lecturers from HZ provide the lessons. There will also be guest lectures on specific topics, such as data collection. Furthermore, you will make several company visits.

With the Applied Data Science minor, depending on the assignment you work on, you may contribute to these Sustainable Development Goals:

  • SDG 3: Improve healthcare by automatically assessing the quality of healthcare records.
  • SDG 7: Contribute to sustainable energy by analysing electricity grid load or predicting smart meter failures.
  • SDG 12: Contribute to responsible production by analysing growth data of vegetables, fruits or molluscs and identifying risk factors.


  • You can set up a data science process.
  • You know how to collect relevant data.
  • You can perform data analysis.
  • You can assess and apply the results from a data science process.


This minor is open to students from all programmes from all universities of applied sciences. The minor is particularly interesting for students ICT.

You must have completed the propedeuse. In addition, you have experience with programming and with the CRISP-DM methodology at the level of the second-year Data Science course of the ICT programme.

If you have not taken this course, there is the possibility of taking the classes in parallel with the minor. Please note that the sequence will then not be optimal so this is quite a challenge.


There is no required literature for this minor.


  • Monday and Wednesday classes at the HZ. On those days, you and your fellow students also give presentations on the progress of your project. There will also be company visits.
  • Two project days. You work together at school or at home on the assignments explained during the classes.


  • Portfolio (100%). You and your working group create a portfolio in which you show that you have applied the learning objectives in the project. In an individual interview, you answer questions about the portfolio.

Aanvullende informatie

HZ has study programmes in Vlissingen and Middelburg. Students from all over the world study here. We think it is important that you get the best out of yourself and develop your talents. At HZ, you matter.

Do you have any questions? Or would you like to discuss whether this minor suits you? We will be happy to help. You can contact Gert Jacobusse at