Loyola University Chicago

Mathematics and Statistics

BS in Data Science

The B.S. in Data Science provides students with a solid undergraduate background in programming and data manipulation, applied statistics and inference, and practical domain experience to fluidly apply these skills. As has been observed in the organizing departments, students who engage in these pursuits become empowered through greater economic opportunities ranging from founding startups to gaining access to organizations that are making significant impacts in the world.

Curriculum (Effective Fall 2020)

Math Requirements

Stats Requirements

  • Introduction to Probability & Statistics: STAT 203
  • Applied Regression Analysis: STAT 308
  • Categorical Data Analysis: STAT 310
  • 6 credits of STAT 300-level electives (excluding STAT 335 and 337)

Computer Science Requirements

  • Computing Tools and Techniques: COMP 141
  • Object-Oriented Mathematical Programming: COMP/MATH 215
  • Data Structures & Algorithms for Informatics: COMP 231
  • Database Programming: COMP 353
  • 6 credits from COMP 300-level electives

Data Science Core

  • One of the following two courses:
  • Social, Legal, and and Ethical Issues in Computing: COMP 317
  • Big Data Analytics (capstone): COMP 358
  • Data Science Consulting (capstone): STAT 370

Note: 56 total credit hours

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Curriculum (Prior to Fall 2020)

Math Requirements

Stats Requirements

  • Introduction to Probability & Statistics: STAT 203
  • Applied Regression Analysis: STAT 308
  • Categorical Data Analysis: STAT 310
  • 6 credits of STAT 300-level electives (excluding STAT 335 and 337)

Computer Science Requirements

  • Computing and Data Analysis for the Sciences: COMP 180
  • One of the following two courses:
    • COMP 170: Introduction to Object-Oriented Programming
    • COMP 215: Object-Oriented Mathematical Programming
  • Data Structures: COMP 271
  • Database Programming: COMP 353
  • 6 credits from COMP 300-level electives

Data Science Core

  • One of the following two courses:
    • STAT 338: Predictive Analytics
    • COMP 379: Machine Learning
  • Social, Legal, and and Ethical Issues in Computing: COMP 317
  • Big Data Analytics (capstone): COMP 358
  • Data Science Consulting (capstone): STAT 370