Milou did a bachelor in Nutrition and Health at WUR and proceeded with the Msc Data Science for Food and Health. She is following the nutrition and health track with a special interest in nutrition and disease.
First year of the programme
I really enjoyed the first year of the master's Data Science for Food and Health. Coming from a nutrition background, I already had a lot of the domain knowledge, but I specialised myself further by following courses such as Nutrition and Cancer. The great thing about this master's programme for me was that I didn't need to have a stong background in data science, because I gained all the relevant data science knowledge and skills during the first year of the programme. In the first course ‘Data Science for Health: Principles’, we learned about all the basics of data science and immediately got to apply it in a practical way with relevant case studies. In later courses, this knowledge was expanded. For example, the course ‘Statistics for Data Science’ provided us with more in-depth knowledge of the statistics behind many data science methods.
Since I follow the nutrition and health track, I specialised further by following courses related to nutrition and health. I followed the thesis preperation course ‘Data Science for Nutritional Epidemiology’. During this course, we already got to apply much of what we learned to the field of nutrutional epidemiology. We worked with data from the COLON study, which is a cohort study performed at the WUR. My group and I investigated the relationship between lifestyle factors and cancer related fatigue in colon cancer survivors. I thought it was really cool that we worked with real-life data during this course, and I'll be able to bring much of what we learned during this course to my thesis next year.
I'll be writing my thesis about a cohort study that followed people with Lynch Syndrome over the course of 13 years. Lynch syndrome is a genetic condition that increases the risk of many types of cancer. During the study, a lot of data was collected from the participants, such as data about diet and lifestyle. I'll be using this data to identify which lifestyle factors are predictive for NOT developing cancer during their lifetime. I'm excited to start this project, as this will be the first time that data science methods are used for this study, so hopefully, this will lead to interesting insights.
Overall, I'm really enjoying the master's Data Science for Food and Health. I especially like how you get to learn and apply data science skills at the same time. In the first year, you immediately start with interesting and relevant case studies, so it's not only theoretical. I also think the programme is set up very well. You start with learning the basics, and you grow your knowledge and skills with each course, so that by the end of the first year, you really feel like you have mastered data science enough to apply it on your own in your intership and thesis.