Cross Disciplinary Studies Minor in Data Science

Offered at: San Luis Obispo Campus

Through an inter-college collaboration, the Computer Science and Statistics departments offer a cross-disciplinary minor in Data Science -- a rapidly evolving discipline that uses elements of statistics and computer science to gather, organize, summarize, and communicate information from a variety of data sources and data types. Job opportunities for data scientists are growing as the availability of data becomes ever abundant via the internet, consumer transactions, sensor arrays, medical records, embedded biometrics, bioinformatics, etc.

The cross-disciplinary minor provides an opportunity for statistics, computer science, and mathematics students to complement their major training with foundational skills for data science. Mathematics and statistics majors will acquire essential programming, database, distributed computing, and data mining skills from the Computer Science Department. Computer science and mathematics majors will acquire essential probability, regression modeling, and statistical programming skills from the Statistics Department. And, statistics and computer science students will acquire specialized calculus, discrete mathematics, and optimization methods from the Mathematics Department.  

Program Learning Objectives

1. Select and use statistical modeling and data analytical methods and techniques appropriate to the scale of the problem.
2. Operate with diverse types of data (for example, weblog, spatio-temporal, basket, transaction, and master)
3. Apply data science methods (acquire, integrate, analyze, visualize) to at least one application domain (e.g., Biology, Business, Science, Geostatistics)
4. Apply computer science principles to design, build and evaluate software
5. Apply statistical models to analyze data
6. Apply mathematical principles to justify statistical and computational models and algorithms
7. Build, maintain, and query common database structures
8. Communicate analysis findings appropriately using oral, written and visual modes.
9. Recognize professional responsibilities and make informed judgments in data science practice based on legal and ethical principles.

Minor Requirements and Curriculum

• At least half of the units must be from upper-division courses (3000-4000 level).
• At least half of the units must be taken at Cal Poly (in residence).
• No more than one-third of the units will be taken with credit-no credit grading (CR/NC), not counting courses with mandatory CR/NC. Departments may further limit CR/NC grading if desired.
• A minimum 2.0 GPA is required in all units counted for completion of the minor.