Applied Data Science
So what is that data can do for the world live in? Medical specialists f.e. use data science, to predict a person’s health based on decades of experience and historical data. In aviation data is crucial to ensure passengers get on board on time and to predict when maintenance is needed for the most effective use of the airplanes. But data is also near you. Think about Siri, Chatbots, Tesla or Google Maps. These services are used daily, most likely also by you, and are based on years of data processing and machine learning.
We have created the ultimate conditions to experience and learn Applied Data Science in real life challenges. The entire minor we apply a structured process for data solutions by using the “Cross Industry Standard Process for Data Mining (CRISP-DM)”, known for understanding the challenge and/or problem, setting realistic data mining goals and reserving the time which is actually needed for data preparation. All in order to achieve an iterative process to reach data mining goals and further improving the machine learning models.
During the minor you will learn about (Advanced) Machine Learning & Deep learning. Most people know about (linear) regression models. In this minor you will be introduced to more advanced models, ranging from ensemble models, such as random forest to gradient boosting. Which could be applied in in predicting remaining “useful life” of infrastructural assets like a lock. For challenges with object recognition with a huge amount of images, you will be introduced to use “Deep Learning” to train your model.
Also note that many learning goals are optional: you have the freedom to choose the ones that match your research. The context of your research will be a real-life problem so the context of your research will be determined on demands, based on the needs in the work field when you start your minor
Location: HZ (Middelburg)
Language: English - depending on the project Dutch is possible as well
Participation requirements Technical domain: HBO-ICT
To participate in this minor, you must have completed your first year. You have a more than average interest in Data Science. Furthermore you have experience with the CRISP-DM Methodology and basis programming skills, at least Python, you may be asked to show proof of your python knowledge.
Min. grade: 5,5