Artificial intelligence (AI) and data are everywhere these days, think for example of the face-ID on your phone, the recommendations on Netflix, the advertisements you see on social media, and your health insurance provider's chatbot. Professionally, you will undoubtedly come into contact with the impact of AI and data to a greater or lesser extent.

Do you want to prepare for the future where you will be dealing with AI and data in your profession? So that you can use the power of data to become a better professional? Will your future profession perhaps change drastically due to the use of data and algorithms? And how can you ensure that those algorithms are applied fairly and transparently?

This minor has been developed for all students who, like us, think that AI and data will have a great impact on our future work. To be able to cope well with that trend, it is important to learn what AI is, how it works, what is possible, and how it sometimes doesn't work. You will learn this through a combination of theory and practice. In the theory part, you will learn the concepts of AI and Data Science, and ethical issues that may arise. In the practical part, you will work hands-on with data and apply what you have learned to questions from the profession for which you are currently being trained.

For example, Albert Heijn recently started experimenting with 'dynamic pricing', where an algorithm calculates how much a product should be discounted based on weather conditions, location, and other variables. For example, if it suddenly starts raining, the store may decide to discount the barbecue meat. You will see the new price on an electronic sign.

Examples of professional AI questions that HG students and researchers have worked on in recent years include:

• Can we predict the return of leukemia?
• How can we get better image recognition with less use of contrast fluid in MRI scans?
• Which students return their public transport passes on time?
• Which clients are at extra risk of a debt collector knocking on their door?
• What is the right energy mix for a building and when should which spaces be heated?

Choice and structure

This minor has been developed according to the idea of 'tailored learning routes'. We have two important principles for this:

1. Freedom of choice for you as a student. In the first quarter, you can bring in your own assignments and datasets within the courses so that they fit your profession. In the second quarter, you largely determine your own learning goals and how you will achieve them in consultation with the teachers.
2. You work at the technical level that suits you. If you are following a non-technical course such as Nursing, HRM, or Law, you can choose the technically 'light' variant where you work with tools such as Tableau or Power BI. If you are following an ICT course, you can go into more depth with, for example, neural networks or specific variants of AI.

The education is composed of four parts that you can choose from. Due to the structure, you can choose from:

• Introduction to AI (5 EC),
• Introduction to AI + AI and your profession 1 (10 EC),
• The entire first quarter (15 EC), or
• The entire semester (30 EC).

If you want to make a different combination, please contact us so that we can discuss your prior knowledge.

AI and your profession (5EC)

In this course, you will learn the basics of what AI and Data Science are. Through many examples, you will learn the different concepts and applications. Using guest lectures from various experts, we will explore how AI and data science are applied in healthcare, business, and government. We pay special attention to the ethical aspects of using AI. You will end the course by conducting an ethical analysis of an AI application in your field.

From data to value (5EC)

In this practical course, you will learn the basics of data collection, processing, visualization, and analysis. You will work hands-on with tools that are suitable for your technical level, and you will select a dataset from your field in consultation with the instructors. Ideally, a research group from your school will also be involved in this course.

Project (5EC)

This project involves developing a data-based solution such as a dashboard or interactive webpage for a problem in your field of study. Students with more programming experience can expand their solution by applying AI.

AI and your profession 2 (15EC)

In this second quarter, you can largely determine your own learning goals. You work in a learning community on a larger practical assignment that fits your profession. Depending on the assignment and your wishes, you can delve into specific AI applications in your profession such as image recognition, autonomous systems (e.g. self-driving cars), judiciary, data-driven business models, AI in games, etc. In stand-ups and demos, you show your progress and learn from fellow students about their issues in other fields. Depending on the needs, we organize workshops with experts from our network. In the field of ethics, we delve deeper into concepts such as trustworthy AI, explainable AI, and ELSA aspects.

The student participates effectively in a community of learners from different professional fields, shares insights, and accepts and provides feedback.

Completed first year programme Bachelor.

To translate AI into your future profession, it is necessary that you are in the third or fourth year of your degree program.

No prior knowledge is required. However, it is desirable that you have an interest in data and want to learn more about handling tooling such as Power BI.

Use license on LinkedInLearning a €25, other literature will be provided digitally.

Portfolio

Mondeling Assessment

Bij geen deelname van Engelstaligen wordt de voertaal Nederlands.