IS 5320 Principles of Data Analysis 3.0 Credits
This course provides an introduction to the quantitative foundations of data science, including linear algebra, calculus, probability theory, and fundamental statistical methods. Students will explore techniques for data summarization, and exploratory analysis while gaining proficiency in configuring and managing statistical programming environments. Emphasizes statistical computing, algorithmic approaches, and the application of computational methods using industry-standard analytic libraries. The course prepares students for professional practice in data-driven fields.
Repeat Status: Not repeatable for credit