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Data Science

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Ole Forsberg

Associate Professor of Mathematics; Chair of Statistics; Chair of Data Science

2 East South Street

Galesburg, IL 61401



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Ford Center for the Fine Arts


How we work

  1. We are an interdisciplinary program. Our students have very diverse interests, and data science is a reflection of that. The program covers areas in mathematics, computer science, and statistics; all while being in tune with ethical issues and fields of application. We address human impacts as well as numbers. Problems in data science require different modes of thinking to solve, which is very characteristic of a liberal arts education.
  2. We teach a program that is in high demand. Data science is becoming increasingly popular, and can lead to plentiful career opportunities that are personally and financially rewarding. We teach our students how to address a wide range of questions with different data sets, which can lead to careers in medical research, sports analytics, marketing, finance, environmental analysis, political research, and many others.
  3. Our program attracts students from a list of diverse studies. Students can participate in our data science program in conjunction with several different majors and minors on campus. Some examples include computer science, environmental studies, political science, economics, business, and areas of the humanities. Data science is so diverse because the data worked with does not always have to be numbers and can include words, image data, and sounds. An example is the problem of detecting spam emails using the presence of certain key words associated with known spam.
  4. Our students can learn in and outside of the classroom. While the data science program has a diverse faculty to teach our students in the classroom, there will be plenty of opportunities for internships and experiences in the community away from Knox. Those opportunities can be found, for example,  in the business and finance sectors in forecasting market activity or classifying industries and institutions in financial difficulty, or in the marketing field in identifying potential customers and their preferred purchases.

How We Learn

The students in the data science major program can start with zero background in the field of study. Every introductory course is just that—an introduction to the study of data science and the background that it relies upon. Students that are attracted to the program are largely quantitative, want to learn about programming, enjoy the use of machines to solve large problems, love to work with and organize data (both numerical and non numerical), and cope well with technicality. 

Our data science program does not require any additional costs. Students will primarily use two different computer programs. These two programs are what is used by professional data scientists, and students may download open source, fully functional versions to use on their own machines. So they will be able to walk away not only with knowledge and skill, but with two tools that are used professionally in the industry.

Learning Goals

Data Science majors will be able to:

  • Prepare a data set for analysis: clean the data, understand variables and transform them when necessary, and deal with missing data;
  • Understand and use standard techniques such as clustering, neural networks, logistic regression, Bayesian classification, decision trees, support vector machines, and nearest neighbor classification to identify patterns in data and develop decision-making models;
  • Evaluate and refine initial models;
  • Use software (such as R and Python) to carry out analyses proficiently and correctly;
  • Apply ethical principles to understand the biases inherent in the use of data and the selection of a model and the possible negative consequences of the analysis;
  • Communicate effectively the results of an analysis in both oral and written forms

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Professor John Dooley and student, in a computer science class.
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Printed on Sunday, July 14, 2024