This course introduces students to essential data science skills, focusing on collecting, cleaning, formatting, and managing data. Students will learn to write Python code to process data efficiently, implement algorithms for analyzing patterns, and apply machine learning techniques. Emphasis will be placed on data visualization as a tool for exploring datasets and communicating findings effectively. In addition to technical skills, students will critically examine the ethical implications of data collection and algorithmic decision-making, and consider the societal impacts of data-driven technologies. 

Units: 1

Max Enrollment: 24

Prerequisites: One of the following - CS 230, CS 230P, or CS 230X, or permission of the instructor.

Distribution Requirements: MM - Mathematical Modeling and Problem Solving

Degree Requirements: DL - Data Literacy (Formerly QRF); DL - Data Literacy (Formerly QRDL)

Typical Periods Offered: Fall

Semesters Offered this Academic Year: Not Offered

Notes: