Introduction to Data Science

Catalog description

Students will learn about the data science lifecycle, including data acquisition, cleaning, exploration, analysis, and visualization. The course covers statistical methods, data wrangling techniques, and the use of different Python tools and libraries, including Jupyter Notebooks, Pandas, Seaborn, and others. Students will work with real-world datasets to uncover insights and effectively communicate their findings through visualizations and reports. Prerequisite(s): CIS 3310 (Grade C or higher).<br/>