WPI’s minor in Data Science is open to all undergraduates. It will give you a core foundation in data science competencies to work with large digital data sets by using computational and statistical techniques and tools, such as applying models and algorithms.

As the ability to extract useful information from large volumes of data is becoming increasingly important to many job fields, such as manufacturing, healthcare and business the Data Science minor makes you more marketable to potential employers.

data science


The Minor in Data Science consists of 2 units, all of which must be selected from the list of approved Data Science minor courses (listed below).  These 2 units must be selected to include the following:

  • Three courses, one from each of the three areas (Business, Computer Science, Mathematical Sciences) at the 2000 level or above from the list of approved Data Science minor courses
  • Two courses at the 3000 level or above, as follows:
    • DS 3001 Foundations of Data Science
    • Any other 3000 level or above course from the list of approved Data Science minor courses
  • One course at any level selected from the list of approved Data Science minor courses

 (Students majoring in Business, Computer Science, or Mathematical Sciences should consult WPI rules on minors for double-counting courses.)

Data Science courses:

  • DS 3001 Foundations of Data Science

Business courses:

  • BUS 2080 Data Analysis for Decision Making
  • MIS 3720 Business Data Management
  • MKT 3650 Consumer Behavior
  • OIE 3420 Quality Planning: Design and Control
  • OIE 3460 Simulation Modeling and Analysis
  • ACC 4200 Managing Performance: Internal and Inter-organizational Perspectives
  • OIE 4420 Practical Optimization: Methods and Applications

Computer Science courses:

  • CS 1004 Introduction to Programming for Non-Majors
  • CS 1101 Introduction to Program Design*
  • CS 1102 Accelerated Introduction to Program Design*
  • CS 2102 Object-Oriented Design Concepts
  • CS 2119 Application Building with Object-Oriented Concepts
  • CS 2223 Algorithms
  • CS 2301 Systems Programming for Non-majors
  • CS 2303 Systems Programming Concepts
  • CS 3431 Database Systems I
  • CS 4120 Analysis of Algorithms
  • CS 4341 Introduction to Artificial Intelligence
  • CS 4432 Database Systems II
  • CS 4445 Data Mining and Knowledge Discovery in Databases
  • CS 4802 Biovisualization
  • CS 4803 Biological and Biomedical Database Mining

Mathematical Sciences courses:

  • MA 2071 Linear Algebra
  • MA 2611 Applied Statistics I
  • MA 2612 Applied Statistics II
  • MA 2621 Probability for Applications†
  • MA 2631 Probability†
  • MA 3231 Linear Programming
  • MA 3627 Introduction to the Design and Analysis of Experiments
  • MA 3631 Mathematical Statistics
  • MA 4213 Loss Models – Risk Theory
  • MA 4214 Loss Models – Survival Models
  • MA 4235 Mathematical Optimization
  • MA 4237 Probabilistic Methods in Operations Research
  • MA 4631 Probability and Mathematical Statistics I
  • MA 4632 Probability and Mathematical Statistics II

* Credit may not be earned for both CS 1101 and CS 1102
† Credit may not be earned for both MA 2621 and MA 2631

Application Process