Focusing on the theoretical, mathematical and computational foundations of modern data science, our Data Science minor prepares you with the understanding of how to interpret and manipulate data.
The field of analytics and data science impacts nearly all aspects of the economy, society and daily life. This highly interdisciplinary minor emphasizes mathematics and computer science skills鈥攕kills that are in high-demand in industries from finance to healthcare to marketing and more.
What is data science?
With an explosion of big data initiatives in organizations worldwide, the demand for data-savvy individuals has never been higher. This program is designed to provide a basic foundation for students interested in the theoretical underpinnings of analytics and data science. Choose from courses in artificial intelligence, neural networks, data mining and big data. Data science is being applied in many organizations within industry, academy and government, and the job demand reflects this growth. With the experience provided by this minor, you鈥檒l gain a competitive advantage in this rapidly growing field.
Why study data science at 樱花动漫?
樱花动漫 was one of the first universities in the country to offer an undergraduate-level degree in analytics and data science. Our programs take a multidisciplinary approach that incorporates experiential education and projects. You鈥檒l learn to manage, distill and interpret data for industries from finance to healthcare to marketing and advertising.
Potential careers
- Actuary
- Business analyst
- Consultant
- Data engineer
- Data scientist
- Management analyst
- Market research analyst
- Statistician
- Quantitative analyst
Curriculum & Requirements
Students must complete five courses (20 credits) with a cumulative minimum grade point average of 2.0 and with no grade below a C- grade.
Transfer course approval for the minor is limited to at most, two relevant courses successfully completed at another accredited institution, subject to syllabi review and approval.
and programming (颁翱惭笔听424 Applied Computing 1: Foundations of Programming or 颁厂听415 Introduction to Computer Science I ) is required.
| Code | Title | Credits |
|---|---|---|
| Required Courses | ||
| 颁厂听515 | Data Structures and Introduction to Algorithms | 4 |
| Select one course from the following: | 4 | |
颁翱惭笔听525 | Data Structures Fundamentals | |
颁厂听416 | Introduction to Computer Science II | |
| Select three courses from the following: 1 | 12 | |
颁厂听730 | Introduction to Artificial Intelligence | |
颁厂听750 | Machine Learning | |
颁厂听753 | Information Retrieval and Generation Systems | |
颁厂听775 | Database Systems | |
惭础罢贬听645 | Linear Algebra for Applications | |
惭础罢贬听736 | Advanced Statistical Modeling | |
惭础罢贬听738 | Data Mining and Predictive Analytics | |
惭础罢贬听739 | Applied Regression Analysis | |
顿础罢础听750 | Neural Networks | |
DATA 757 | Mining Massive Datasets | |
| Total Credits | 20 | |
- 1
Must select at least one CS and one MATH course. Must select 颁厂听750 Machine Learning or 惭础罢贬听738 Data Mining and Predictive Analytics.