Hendrik Werner

Hendrik Werner
Data Science has been extremely transformative over the last decades, and I think it will continue to be.
Hendrik Werner
Data Science
Country of previous education
Previous education
Bachelor's Computing Science at Radboud University

Hendrik Werner is a second-year Master's student Data Science at Radboud University.

What do you like about the specialisation and why? 

The Computing Science programme at Radboud University has repeatedly been voted one of the best in the Netherlands, and for good reason. We have impressive people working at the institute, and great, modern facilities. The Data Science master specialisation was challenging and difficult, but interesting and motivating enough to make it worthwhile.

What do you think about the atmosphere in class?

Students are smart and motivated, participating actively during lectures. Lecturers and professors are very close to the students and approachable. They are very knowledgeable and eager to help students and share their knowledge.

What do you find most challenging in your Master’s specialisation?

Mathematics and time-management were the most difficult aspects of my master specialisation. We have a lot of projects to complete, and they take a lot of time, if you want to do them properly. Additionally, we have all the exams. Can be overwhelming at times.

Are you currently doing an internship? Or what is your thesis about?

I have completed my research internship at Spinque B.V., where I integrated AI-based Named Entity Recognition into their Spinque Desk offering, which can be used to construct custom search strategies. I am currently writing my Master's thesis on the influence of tokenisers in NLP pipelines using text-to-text transformers. With a particular focus on token-free models.

What are your plans once have received your Master's degree?

Data Science has been extremely transformative over the last decades, and I think it will continue to be. It has been adopted in nearly every aspect of commerce and academia, and has rapidly enabled use cases and application though impossible just a few years back. Long-term, if we want to automate mundane and repetitive tasks, so humanity can focus on creative and interesting topics, I think Data Science will play a key role in that transition. (This is already happening.)