Mathematics and Statistics are the foundation for data science. Data scientists use their formidable skills in maths, statistics and programming to clean, manage and analyze an enormous amount of data to uncover hidden solutions to business problems. An institution which blends a strong base of mathematics in its data science program to take on complex data challenges faced by enterprises today is Saint Mary's College, Notre Dame, IN.
In a recent interaction with Analytics Insight, Kristin Kuter, Director of the Master of Science in Data Science at Saint Mary's College explains how the mathematically rigorous Data Science Program offers an enduring skill set to students allowing them to develop deep analytical skills to generate valuable insights from big data.
I think that one overlooked area where data science has the potential for great impact is healthcare analytics. Healthcare institutions have been and are now collecting massive amounts of data, but I don't think many institutions have the resources needed to analyze the data in order to improve the quality of care being offered. This I think is one area that Big Data Analytics will be a major contributor to in the near future, helping to improve efficiency and effectiveness in the healthcare industry.
Our program is housed in the Mathematics and Computer Science Department at Saint Mary's, and as such the data science education we offer is rooted in fundamentals. Our graduates are prepared to not only use the industry standard data science tools, but are knowledgeable about the theoretical underpinnings of the tools, which means that when they leave Saint Mary's they will be prepared to improve upon the tools currently used and help advance the field.
I honestly think that Saint Mary's has many advantages over other institutes, including our size, location, and mission. I believe that our greatest edge is our relatively small size, which intentionally allows the faculty to provide individualized education to each student. Our location is also an advantage, which may seem surprising given that we are not located on the west coast, but rather in South Bend, IN. However, there is a growing number of tech and data science-related industries that have been popping up in the region just over the last few years. We have a wonderful mayor devoted to the field and growing the local economy, as well as a Regional Development Authority for the greater South Bend – Elkhart region that also helps promote growth in the industry. Finally, the mission of Saint Mary's, with a Catholic tradition, gives us an edge for candidates interested in using data science for social good and to make a difference in the world.
I am the Director of the Master of Science in Data Science at Saint Mary's College, which means that I manage the budget and curriculum of the program, I review all applications to the program, I advise all the students and help them secure placements for their capstone practicum projects, and I collaborate with corporate and community partners to ensure that our program is meeting the current needs of the industry. My background is in probability and statistics, so I also teach our two-semester sequence on applied statistics, which covers the basic statistical techniques, like hypothesis testing and ANOVA, in the first semester, and then in the second semester look at predictive modeling techniques, such as ridge regression and the lasso. We started developing our program about 6 years ago and launched in August of 2015.
Study mathematics! We get a lot of applicants to our master's program that have great experience with programming and databases, but have gaps when it comes to the math essentials, like calculus and linear algebra. Many of the algorithms and statistical techniques in data science are grounded in these math essentials and so being able to fully understand and implement the tools of the trade requires first having an understanding of the math.
Besides the privacy and ethical concerns around the use of data science, which is a major issue primarily in social media right now, I actually think one of the biggest challenges is the lack of standardization in the term data science and the various educational pathways to obtaining skills in data science. I feel this is a challenge because individuals interested in entering the industry are not sure of the best way to prepare themselves. Educational institutes are trying to catch up to the relative novelty of the field, by developing data science graduate programs, but I think more undergraduate programs in data science are also needed.
Under my leadership, we launched the program and graduated our first class of students, though much of the efforts to accomplish these achievements are shared by the hard-working faculty members in my department. We hosted a Data Science Hackathon this past spring, which was a collaboration with a local healthcare analytics company, and was attended by nearly 100 undergraduate and graduate students from schools in Indiana and Illinois. The winners of the event were offered jobs at a local data analytics firm, and the connection was made during a networking portion of the hackathon. Finally, I would be remiss if I didn't mention some of the great things that our graduates are doing. We have graduates working to develop data science teams at major state-wide insurance companies, working as contractors on government funded initiatives to investigate solutions to the opioid crisis, and creating their own consulting firms to provide analytics services to governments and businesses in developing countries. We are so proud of our graduates and the work they do.
As I mentioned earlier, I think a trend that we will see is a rise in the number of undergraduate programs in data science, which may have an impact on employers.
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