AI Engineer (najaar & voorjaar)

The machine learning and deep learning modules already provided you with a solid foundation for the concepts of modern AI and how to implement it in a practical way. In this specializing module Advanced AI, we build on these foundations and focus on specific application domains such as advanced computer vision, advanced NLP (natural language processing), generative neural networks, belief networks and multiple-input multiple-output systems.

In addition to further deepening of data-driven machine learning systems, we also study and implement reinforcement learning and deep reinforcement learning systems in this course. Instead of learning from data, these self-learning systems use trial & error to look for an optimal strategy that will give them a maximum reward. These (deep) reinforcement learning strategies mainly find applications in self-learning robots, optimisation of industrial processes, computer games, self-driving cars and personalised recommendations. In addition, we go deeper into a number of popular optimisation and simulation techniques that can significantly improve the performance of your used learning algorithm.

This module is also hand-on with the focus on being able to implement and integrate the AI systems seen in practice. In that respect, it is intended that you come into contact with various state-of-the-art AI frameworks for the development of both deep neural networks and for the design and simulation of (deep) reinforcement learning systems.

The internship is the ideal way to test the practical knowledge and experience. Because a solid company internship requires a certain period of integration, 15 weeks are provided for this. The objective of the internship is twofold: you will gain insight in the business and work on one or more AI business projects or research assignments.

To ensure the smooth running of the internship, an internship agreement is completed and signed by the three parties involved prior to the internship (the internship company, the student and the study programme). The internship agreement clearly states the expected tasks and results of the intern (=the project sheet). In general, we impose three conditions on the internship company: professional supervision, your own workplace and a well-defined assignment of a sufficiently high level.

During the internship period, the student is assigned two supervisors: the internship mentor who is responsible for the daily supervision within the company and the internship supervisor who supervises the student from a distance (based on the internship report).