Classification: Major
Degree: Bachelor of Science
An exciting career that blends the science of data-driven decision-making with the art of problem-solving, data analysts gather the research and identify the key insights that help organizations plan new marketing strategies, make business decisions, and map out their path to future success.
Our new data analytics program is structured to provide the critical thinking skills, technical background, and research experience you need to hit the ground running when you graduate. About 50 percent of your courses will be in-person at Wells, and the rest of your work will be done online. This hybrid format gives you the best of both worlds -- dedicated faculty mentors to guide your learning on campus, and online access to more top data experts and the most up-to-date techniques in this field.
In addition to conducting data analysis and exploring experimental design, you’ll participate in regular “data labs” where you’ll analyze, display, and manipulate data sets individually and in teams. You’ll gain even more practical experience through local internships and the completion of a capstone research project focusing on real-world data drawn from sports, politics, business or public health.
Required Courses
Required credits in Major: 46-48.
- CS 100 Introduction to Computers and Microsoft Office (3 credits)
- CS 131 Programming |: Procedural Methods (3 credits)
- CS 132 Programming II: Advanced Design (3 credits)
- CS 133 Programming for Everyone II (3 credits)
- CS 234 Data Structures (3 credits)
- MATH 111 Calculus |: Introduction to Calculus (4 credits)
- MATH 251 Mathematical Statistics (3 credits)
- DATA 131 Foundations of Data Analytics I (3 credits)
- DATA 132 Foundations of Data Analytics II (3 credits)
- DATA 333 Principles and Techniques of Data Analytics I (3 credits)
- DATA 334 Principles and Techniques of Data Analytics II (3 credits)
- DATA 402 Data Analytics Practicum (3 credits)
Electives, Choose 3 from the list below:
- BUS 204 Business Analytics (3 credits)
- CS 303 Machine Learning (3 credits)
- CS 322 Algorithms (3 credits)
- ECON 314 Econometrics (3 credits)
- PHIL 240 Ethics, Equality and Justice (3 credits)
- PSY 365L Quantitative Methods in Psychology (4 credits)
- SS 394 Research Methods for the Social Sciences (4 credits)