Curriculum

Program Details

  • 30 Credits
  • 4 Semesters - 2 Years
  • 8-Week Classes
  • No Summer Classes
  • Fully Online

Questions?

Contact: Graduate Admissions
Call or Text (866) 380-5323
Email: gradadmissions@gonzaga.edu

2 Year Course Progression

  • Classes are 8-weeks in length.
  • Semesters are broken into two sessions, A and B.
  • You will take one 8-week course in the A session and one 8-week course in the B session.
  • In your final semester you will take a full semester capstone course along with your last two classes.
  • Classes are not offered in the summer.

Semester 1

Fall A

  • DATA 522: Foundations of Data Science - 4 credits

Fall B

  • Data 525: Statistical Computing - 3 credits

Semester 2

Spring A
  • Data 581: Data Analytics & Communication - 3 credits

Spring B

  • Data 532: Data & Algorithm Ethics - 3 credits

 

 

Semester 3

Fall A

  • DATA 526: Data Mining & Statistical Learning - 3 credits

Fall B

  • Data 582: Data Intensive Systems - 3 credits

Semester 4

Data 583 is a full 16 week course broken up into two 8-week sections.  The entire 16-week course is 3 credits.

Spring A
  • Data 561: Machine Learning - 4 credits
  • Data 583: Data Science Capstone Part 1 - 3 Credits

Spring B

  • Data 562: Machine Learning II - 4 credits
  • Data 583: Data Science Capstone Part 2 
 

Prerequisites

Depending on your bachelor's degree and work experience, you may need to take some prerequisite courses for success in the program.

Prerequisites

  • Minimum of one semester or quarter of statistics - for example Gonzaga’s MATH 121, 221, or 321 or BUSN 230
  • Minimum of one semester or quarter of calculus - for example Gonzaga’s MATH 114, 148, or 157
  • Minimum of one year of computer science coursework or equivalent programming proficiency as demonstrated by other coursework or professional experience.
  • Familiarity with Python.