0 or 3 credits
Fall 2026 Lecture Laboratory Distance Learning Lower Division
(STAT 24200) This course provides a broad introduction to the field of data science. The course focuses on using computational methods and statistical techniques to analyze massive amounts of data and to extract knowledge. It provides an overview of foundational computational and statistical tools for data acquisition and cleaning, data management and big data systems. The course surveys the complete data science process from data to knowledge and gives students hands-on experience with tools and methods. Basic knowledge of Python required. Computer Science majors cannot count this course as a degree requirement but can take it for credit as a free elective if taken before CS 37300, 34800, 47100, 47300, 44800.
Learning Outcomes1Use Python, R, and selected tools to scrape, clean, process, and visualize data.
2Apply data management techniques to prepare, parse, manipulate, and store data.
3Use statistical methods to summarize data and identify relationships.
4Explain how to formulate new hypotheses and draw accurate conclusions from data.
5Apply statistics and computational analysis to make predictions based on data.
6Apply basic computer science concepts such as modularity, abstraction, and encapsulation to data analysis problems.
7Effectively communicate the outcome of data analysis using descriptive statistics and visualizations.
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made by Purdue students.