Advisory: Enrollment requires appropriate placement (based on high school GPA and/or other measures), or completion of an intermediate algebra course, ENGL C1000, READ 101
Transfers to:UC,CSU
This course introduces basic programming and statistical concepts, including programming for data cleansing, manipulation, visualization, and statistical computation for intelligence gathering. Students apply common built-in language functions for analysis of real-world datasets, including global and local economic data, commercial business, document collections, and social networks. This course also delves into machine learning and data-driven decision-making using statistical concepts like hypothesis testing, confidence intervals via bootstrapping, regression and inference for regression, and predictive modeling. In the course, students also learn about social issues surrounding data privacy and ownership.