Data Science Major
Through their coursework, our majors gain expertise in each of the following areas:
- Programming fundamentals including data structures, algorithms, OOP, and databases
- Machine learning and deep learning
- Mathematical foundations including statistics, statistical inference, linear algebra and computational data analysis
- Communicating results, including written, verbal, and visual communication
- Data curation and management
- Reproducibility/documentation of analyses
- Ethics (privacy, data access, data control)
Course Requirements
A minimum of twelve courses to include:
- CS 125/DASC 125 - Introduction to Computer and Data Sciences
- CS 128 - Computer Science 2
- CS 135/MATH 135 - Applications of Sets, Logic, and Recursion
- ART 141 - Graphic Design I
- MATH 215 - Linear Algebra
- CS 222/PHIL 222 - Ethics, Values, and Issues in Cybertechnology
- DASC 225 - Data Analytics with Visualization
- CS 314 - Database Systems
- CS 377/DASC 377 - Applied Data Analysis
- CS 387 - Deep Learning
- MATH 403 - Computational Data Analysis
- One statistics course: MATH 141, MATH 325, ECON 227, PSYC227, or BIOL 323
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