CSpotlight: The universal versatility of data science
After a stint working in industry, Miguel Miguélez Díaz decided he wanted a stronger foundation in data science. When the Spanish native visited the University, he discovered that Minnesota was the perfect fit. The flexibility of the curriculum appealed to him—he started with the post-baccalaureate certificate, and then transferred into the master's program.
Why did you choose to study data science at the University of Minnesota?
I always wanted to study abroad, so I researched several universities in Europe and the United States to learn about different program options.
In 2018, I visited the U.S. for the first time and decided to tour the University of Minnesota campus. I was impressed by the facilities and the approachability of the faculty members. During my visit, I talked with Daniel Boley, the Director of Graduate Studies, about the curriculum for the data science program.
Prior to my visit, I already had some knowledge about the Midwest and its people, as I had some friends in Madrid who were originally from the region. All this insight helped me to decide that the University of Minnesota was the best option for my graduate studies.
How did you initially decide to pursue the Post-Baccalaureate Certificate in Data Science? What made you decide to continue with the Master of Science program?
After working for almost four years in a related field, I felt the need to improve my skills in data science. In a world that is constantly changing, it is important to be prepared to face new challenges and to continue learning every day. It was not an easy decision to leave the company where I worked, but I have been very happy with my choice.
I initially selected the Post-Baccalaureate Certificate in Data Science program. I liked that it offered the flexibility of completing coursework in one year, and gave the option to easily transfer into the M.S. in Data Science program. One great advantage is that all the credits I earned for the certificate also count towards the M.S. degree.
After finishing my first semester, I found that the classes were engaging and the coursework was challenging yet rewarding. Therefore, I decided to transfer to the M.S. program to further my knowledge and foundation in data science even more.
Tell us about the research you conducted at the Universidad Politécnica de Madrid.
The main goal of the research project was to improve the workflow of aeronautical production facilities. Most of the results were also applicable to other kind of facilities as they involved optimizing the production scheduling and resources assignment in an assembly line subjected to different workloads, operators’ qualifications, shared resources and other factors.
Working on this project helped me to improve my problem-solving expertise, which has increased my confidence to always find a tailored solution for any given problem, regardless of its apparent initial difficulty.
What advice do you have for incoming data science students?
My advice would be to get involved in a project to complement what is learned in class. The department has multiple areas of research which will let you dive deep into any field of your choice.
Over the summer, I had the opportunity to work with assistant professor Dongyeop Kang on an natural language processing (NLP) research project and will continue working with him this fall. Just look for your field and let the professors know about your interest!
What are your plans after graduation?
I think data science students are very versatile employees as we can make a great impact in multiple sectors: healthcare, logistics, utilities, finance, and more. After graduating, I would like to help a company create more efficient processes and develop decision-making tools to make informed choices. In addition, I will keep expanding my knowledge in this ever-changing field.