My story
Issue 1
Mete Veyisoglu spent a year studying MSc Data Science at UCL in 2018/19
When I decided to apply for UCL’s MSc in Data Science, I had been working at Koc University (Istanbul, Turkey) as institutional planning manager for five years. My duties comprised various data-related tasks such as forecasting, financial planning and data-driven decision-making to shape future strategy. I had huge amounts of academic data at my disposal, and I had to be both creative in coming up with various statistics to depict the institution’s outlook and also very careful not to make any scientific errors as it would lead to incorrect decisions.
In short, I needed more expertise in the fields of statistics and machine learning. I chose UCL for its strong tradition in statistics (this was a pioneering statistics department, where many of the founders of the discipline worked), its historic Bloomsbury location that is very central but also pleasantly remote from the busy tourist and commuter crowds, and its general reputation as one of the best universities in the world.
I had to decide between two programmes, MSc in Data Science offered by the Statistics department and MSc in Data Science and Machine Learning offered by the Computer Science department. I chose the first one mainly because I am more oriented towards mathematics and statistics, and I wanted to learn about the classical fundamentals. As the probabilist and risk guru Nassim Nicholas Taleb says in his bestseller ‘Skin In The Game’: “No statistics without logic, no mathematics without proof, no facts without rigor”. Today, the amount of data available in any domain is huge and it is very easy to mistake noise for signal and find interesting but misleading patterns in data. I was hoping to gain the skills to identify these pitfalls.
Reality usually falls short of meeting our expectations, but my year in the Statistics department was an exception to this rule. Not only did I see that all my reasons for choosing UCL and the Data Science programme proved to be correct, but I also found that my classmates were brilliant people. I learned as much from them as I did from the classes.
One huge advantage of the programme is that it’s cross-disciplinary, so we had colleagues from a variety of backgrounds such as mathematics, physics, economics and engineering. This made the postgraduate study room a great place to learn from each other. Also, UCL and the Statistics department are doing a great job of listening to students. Faculty members, MSc tutors and administrative management genuinely work towards finding solutions to student-reported issues. This determination to resolve issues, in turn, increased my motivation to learn.
In the fall and spring terms, I took very interesting modules including Introduction to Machine Learning, Introduction to Statistical Data Science, Financial Data and Statistics, Extreme Value Theory, and Copula Theory, among others. I loved the system in the UK where you take all the year’s exams in May, so you are not ‘done’ with the fall semester modules in December. This is a good way to ensure that students learn for life, not just for school.
The summer term was dedicated to the research project, and it was both challenging and fun. I chose to work on an issue related to my job at Koc University: using statistical and machine learning methods to predict which college students are more likely to fail and eventually drop out of college. I think I worked harder in summer than in either of the other terms – it’s really challenging to deliver a UCL-level MSc dissertation in three months! Nevertheless, I loved the challenge of working on a longer-term project, making small steps of progress every day. I had weekly meetings with my supervisor, Dr. Thomas Honnor, who was very supportive and helped me keep my stamina and my motivation up through summer. In the end, we both were very content with the resulting work. The models that I developed will have huge practical value for Koc University, and the thesis could even serve as a model on how to use data science to increase data-driven policy-making in Turkish Higher Education.
The quantitative skills I gained and the brilliant people I met during my year at UCL indicate that this was not a chapter you close and move on from; but one that will always guide you through your career. I am certain that my classmates feel the same.
Look out for more student stories in future editions of Sample Space.