Data Science

Data Science Image with Logo

We are very excited to be able to offer this new Data Science program, starting with a Minor in the fall of 2020.

Minor Requirements

In order to earn a minor in data science, students must complete 30 credits, including:

Programming: Choose one of the following four courses (4-5 credits)

CPSC 1220 - Data-driven Problem Solving and Programming
CPSC 1420 - Programming and Problem Solving I
ECEGR 2000 - Physical Computing with Python
MEGR 2810 - Engineering Methods

Statistics: Choose one of the following nine courses (5 credits)

CRJS 3020 - Criminal Justice Statistics
ECON 2100 - Business Statistics
EVST 3400 - Research Design and Statistics
MATH 1210 - Statistics for Life Sciences
MATH 2310 - Probability & Statistics for the Sciences and Engineering
MATH 3412 - Mathematical Statistics
PSYC 3050 - Statistics and Research Methods II
PUBA 4400 - Research Design and Statistics
SOCW 4010 - Social Work Data Analysis

Databases: Choose one of the following two courses (5 credits)

CPSC 2300 - Introduction to Databases
CPSC 3300 - Fundamentals of Databases

Data Visualization: Choose one of the following two courses (5 credits)

BUAN 3210 - Data Visualization and Communication
DATA 3310 - Data Visualization

Methodology and Applications of Data Science: Take this Data course (5 credits)

DATA 3320 – Methodology and Applications of Data Science

Data Science Electives: Choose remaining credits from the following courses

BUAN 4310 - Data Mining and Big Data Analytics
CHEM 3000 - Quantitative Analysis
CPSC 4310 - Machine Learning
CPSC 4330 - Big Data Analytics
CPSC 4610 - Artificial Intelligence
ECEGR 4620 - Data Communication Networks
ECEGR 4640 - Internet of Things
ECEGR 4720 - Introduction to Digital Image Processing
ECEGR 4750 - Machine Learning I
ECEGR 4760 - Machine Learning II
ECON 3100 - Quantitative Methods and Applications
ECON 4110 - Applied Econometrics
ECON 4120 - Forecasting Business Conditions
ENSC 2400 - Environmental Sensors
ENSC/EVST 3500 - Intro to Geographic Information Systems
MATH 3411 - Probability
MATH 3450 - Introduction to Numerical Methods
MEGR 4910 - Design Optimization
PHYS 3910 - Computational Physics
PSYC 4030 - Advanced Statistics and Experimental Design

See our Advising Guide for additional details or contact Dr. Sloughter at sloughtj@seattleu.edu