Afbeelding
During the master’s programme you will work on these four learning outcomes:
- Design, develop and test independently and within a team methodologically correct, machine-learning algorithms that automate visual inspections to meet the customer's specifications.
- Create and manage, in collaboration with domain experts, a representative annotated and balanced dataset with the required quality to develop and test machine-learning algorithms.
- Optimize algorithms, independently and based on customer specifications, and make them scalable so they can be applied in practice.
- Develop yourself proactively and with a high degree of responsibility, to guarantee your sustainable employability and thus also contribute to the development of professional practice and the knowledge domain.
By working on your project, you gather evidence in your portfolio for proving the learning outcomes at the end of the semester. Working towards this moment, in five sprints, the progress in your development is regularly discussed and feedup, feedback and feedforward is given. The same learning outcomes are used throughout the programme, but the level of context (independence and complexity) increases as the programme progresses, leading to a master's level in the final semester.
