Core Courses

All students are required to complete a core curriculum consisting of 54 credits in mathematics, computer science, data science, statistics, and philosophy bracketed by introductory and capstone courses designed for the degree. For course descriptions and per-requisite list, see the linked PDF core and track course sheets.

Find the four-year data analytics degree plan here: Data Analytics Core Curriculum 4-year Plan

Lower Division

• Math 171: Calculus I
• DATA/MATH 225 Linear Algebra with Modern Applications or Math 220: Linear Algebra
• DATA 115: Intro to Data Analytics
• DATA 219 Data Structures for DATA Analytics or CPTS 215: Data Analytics Systems & Algorithms

  And one of:
• CPT_S/CS121 Program Design and Development C/C++
• CPT_S/CS 122 Data Structures C/C++
• CPT_S/CS 131 Program Design and Development Java
• CPT_S/CS 132 Data Structures Java

  Recommended/Elective (not required)
• Math 172: Calculus II

Upper Division

• STAT 360: Probability & Statistics
• STAT 435: Statistical Modeling for Data Analytics
• STAT 437: High Dimensional Data Learning and Visualization
• PHIL 450: Data Analytics Ethics

  Computer Science:
• CPTS 415: Big Data
• CPTS 451/CS 351: Intro to Database Systems

  Data Analytics:
• DATA 319: Model-based and Data-based Methods for Data Analytics
• DATA 424: Data Analytics Capstone
• DATA 498: Internship

  Recommended/Elective (not required)
• STAT 419: Multivariate Statistics

 

UCORE Requirements

All WSU undergraduates must satisfy the University Core Requirements [UCORE] in order to graduate.

Several courses are recommended for development of communication skills vital to career success in the data analytics field, including:

• COM 102: Public Speaking in the Digital Age [COMM]
• COM 210: Multimedia Content Creation [COMM]
• H_D 205: Developing Effective Communication and Life Skills [COMM]
• COM 105: Communication in Global Contexts [HUM]
• DTC 201: Tools and Methods for Digital Technology [ARTS]
• CES 421: Intercultural Communication and Globalization [DIV]

Details and a list of course options are available on the UCORE website.

Student Learning Outcomes

At the conclusion of their Data Analytics B.S. degree program, students will be able to:

1.  Understand the theory and basis of data analytics (including computing, statistics and mathematics) to be able to apply in the practice of data analytics.
2.  Identify, locate, evaluate, collect, compile and responsibly (ethically, legally, socially, professionally, and securely) use data and associated materials from multiple sources relevant for Data Analytics
3.  Customize and utilize data analytics and data management software packages in order to manage and apply exploratory, descriptive and inferential data analytics techniques to complex data sets
4.  Appropriately define Data problems, formulate questions, develop and design an analysis plan, and interpret the results of these analyses.
5.  Effectively communicate data analytics techniques and results in a scientifically and technologically informed way to the academic community, business/industry professionals, and the general public in writing, discussion, digital media, and other communication formats.
6.  Work with a team of students in consultation with a client to apply a full range of Data Analytics techniques drawn from computer science, mathematics and statistics to address a real-world application problem.

Syllabi

(Syllabi may vary slightly from semester to semester.)

DATA 115

DATA 115-Global

DATA 219

DATA 301

DATA 302

DATA 303

DATA 319

DATA 319-Global