The College of Arts and Sciences now offers a B.S. in data science.

What is a Data Scientist?

A data scientist analyzes complex systems and solves real-world problems through the analysis of data, and in particular, very large sets of data. Many scientific disciplines, our economy, and even our providers of streaming entertainment increasingly rely on data. You’ll work with a variety of methods including predictive/prescriptive analytics, algorithm design and execution, applied machine learning, statistical modeling, and data visualization.

Why Data Science?

Data science, and its associated fields, is one of the fastest growing employment opportunities in the world. A strong demand in the job market — combined with a shortage of people trained in data science —means you’ll have opportunities in all sectors of society.

According to the Education Advisory Board, some of the top occupations requiring data analysis skills are:

  • Marketing managers
  • Financial analysts
  • Computer systems engineers/architects
  • Business intelligence analysts
  • Computer programmers

And, some top employers for data analytics-related skills are:

  • UnitedHealth Group
  • Microsoft Corporation
  • JP Morgan Chase Company
  • General Electric Company

The new bachelor of science in data science at Valpo is designed to give graduates the interdisciplinary skills that employers need. The data science program integrates statistics, mathematics, computer science, and data science to produce graduates with the skills needed to evaluate and interpret data. You will gain a broad skill set that will be attractive to employers in this thriving field.

Degree Requirements — Bachelor of Science in Data Science

In order to graduate with a bachelor of science in data science at Valpo, a minimum of 40 credit hours is required. Students must take courses in data science and from the partner disciplines of statistics, mathematics, and computer science. Additionally, students should explore an area of application through selection of one or more courses from an appropriate field, as described below. Students are strongly encouraged to take a minor or a second major in their applied field of interest.

Course Title Credits
Statistics Courses (9-10 credits)
One course from the following options is required:
STAT 140 General Statistics 3 Credits
STAT 240 (*) Statistical Analysis 3 Credits
IDS 205 Business Statistics 3 Credits
PSY 201 Statistical Methods 3 Credits
CE 202 Statistical Applications in Civil Engineering 3 Credits
(*) STAT 240 is the recommended option.
One course from the following options is required:
STAT/IDS 340 Statistics for Decision-Making 3 Credits
ECON 325 Econometrics 3 Credits
One course from the following options is required:
STAT 343 Time Series Analysis 3 Credits
STAT 344 Stochastic Processes 3 Credits
STAT 441 Probability 4 Credits
Mathematics Courses (8-10 credits)
The following courses are required:
MATH 131 Calculus I 4 Credits
MATH 220 Discrete Mathematics 3 Credits
One course from the following options is required:
MATH 260 Linear Systems and Matrices 1 Credit
MATH 264 Linear Algebra 3 Credits
Computer Science (11-12 credits)
The following courses are required:
CS 157 Algorithms and Programming 2+3, 3 Credits
CS 158 Algorithms and Abstract Data Types 2+3, 3 Credits
CS 350 Database Management Systems 2+3, 3 Credits
One course from the following options is required:
CS 225 Programming Languages 3+1, 2 Credits
CS 325 Simulation and Modeling 3 Credits
CS 345 Artificial Intelligence 3+1, 2 Credits
Data Science (11 credits)
The following courses are required:
DATA 151 Introduction to Data Science 2+3, 3 Credits
DATA 433 Data Mining and Applications 2+3, 3 Credits
DATA 299 Data Science Colloquium I 0 Credits
DATA 399 Data Science Colloquium II 1 Credit
DATA 499 Data Science Capstone 1 Credit
One course from the following options is required:
DATA 373 Computational Linear Algebra 2+3, 3 Credits
DATA 375 Scientific Visualization 2+3, 3 Credits
DATA 490 Advanced Topics in Data Science 3 Credits
ECON 473 Applied Data Science 3 Credits
Application Area (1-3 credits)
One course from the following options is required:
BIO 321/MATH 321 Mathematical Models of Infectious Diseases 3 Credits
GEO/MET 460 Data Analysis 3 Credits
ECON 473 Applied Data Science (if not taken above) 3 Credits
PHYS 246 Data Reduction and Error Analysis 1 Credit
POLS 260 Research Methods in Political Science 3 Credits
PSY 370 Laboratory in Experimental Design and Analysis 3 Credits

*Additional courses may be approved by the program director.

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