CS 109 - Data Science for Social Good

Credits: 5
Hands-on introduction to data science for everyone, focusing on using data for social good. Learn how to collect, compute, analyze, and visualize data to discover trends and gain insight and knowledge on issues of equity and the impacts of socioeconomic inequalities. Build data-driven cases to advocate for social change and justice. No previous experience is required.

Enrollment Requirement: Eligible for MATH 97 or higher; and eligible for ENGL& 101; or instructor consent.

Satisfies Requirement: Diversity
Course Outcomes:
Students who successfully complete this class will be able to:

Create a computational artifact using computing tools and techniques to solve a problem.
Collaborate in the creation of computational artifacts or when writing a program.
Develop an abstraction when writing a program or creating computational artifacts.
Manage, clean, summarize and visualize simple data sets relating to social issues.
Summarize information from data to explain patterns or trends in social issues using descriptive statistics.
Find patterns and test hypotheses about digitally processed information to gain insight and knowledge on issues of equity and the impacts of socioeconomic inequities.
Explain the insight and knowledge gained from digitally processed data by using appropriate visualizations, notations, and precise language to build a case for advocacy for social change and justice.

Program Outcomes

Use appropriate reasoning to evaluate problems, make decisions, and formulate solutions.
Give reasons for conclusions, assumptions, beliefs, and hypotheses.
Evaluate and interpret quantitative and symbolic reasoning information/data.
Implement calculator/computer technology to solve problems.

College-wide Outcomes

Quantitative and Symbolic Reasoning - Quantitative Reasoning encompasses abilities necessary for a student to become literate in today’s technological world. Quantitative reasoning begins with basic skills and extends to problem solving.