This course introduces students to the principles and practical techniques of data wrangling using Python. Students learn how to collect, import, clean, reshape, merge, and transform data using Python’s core analytical libraries within the Jupyter Notebook environment. Emphasis is placed on mastering data manipulation, handling missing or inconsistent values, integrating multiple datasets, and preparing clean, reliable data for analysis or modeling, including both categorical and time-series data. Through hands-on labs and applied projects, students develop strong programming and analytical skills for efficiently and reproducibly managing real-world datasets.
Prerequisites
CISM148 with a grade of C or better