The University of Texas at Austin 3 credits Statistics and Data Sciences
Explore data science tools and examine data wrangling; exploratory data analysis and data visualization; markdown and data workflow; simulation-based inference; and classification methods. R programming is emphasized and Python programming is introduced. Only one of the following may be counted: Statistics and Data Sciences 313, 322E, 348. Three lecture hours and one laboratory hour a week for one semester. Pre/Corequisites: An introductory statistics course.
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