Data Science for Everyone

Catalog description

This course focuses on the basic principles of data science, its context and applications, and the essential components of the data science life cycle: data generation, collection, curation, storage, management, and analysis. Students will gain skills in data preparation and in conducting exploratory data analysis using real-world datasets that could generate insights and hypotheses. Students will be introduced to data science and analytics tools such as Excel, R/Python, Tableau/Microsoft Power BI, Alteryx, and RapidMiner. This course provides a foundation to advanced courses in data science and data analysis. Prior knowledge of programming or statistics is not required. Prerequisites: none. (F, Sp)