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.