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Computer Education & Training Center


R Programming Classes

R is a programmable environment to analyze data. It can pull data from a variety of sources and help you create visualizations. It supports command-line scripting that allows you to more easily reuse your work for other analysis and handle more complex situations. Learn to use this software tool by taking an instructor-led class from the Computer Education & Training Center at UMSL. [More on R]

Virtual Classes: Our R classes are now available online with an instructor present for the entire course. You will see the instructor's screen throughout the class and you can share your screen if you need individual help from the instructor. You will have time to practice, ask questions, and receive hands-on training. If you don't have R installed on your machine, you can remote into one of our computers.

In-person classes are also available at our West County facility with limited enrollments to promote social distancing. When you register, choose your class section based on how you want to attend the class: virtual or in-person.

  • Select "Live Online" if you want to attend virtually from your workplace or home.
  • Choose "West County In-Person" if you want to attend a class at our West County location.

For more information, email

Introduction to R

(Prerequisite: Intermediate Applications of SQL or equivalent experience.) Discover how to glean insights and meaning from your data using the R data analysis tool. Understand R terminology, the R approach, RStudio, and how to navigate the interface. Work with R syntax and learn to manipulate R objects. Discover how to import working data into R. Develop the skills to work with variable assignments, vectors, and data frames and how to perform operations on all three. Learn to access information in a data frame and how to index, filter, and order your data to generate output. Understand how to represent data with different visualization types and do calculations. Topics include terminology, data layout, pulling basic stats from your data frame, understanding your data objects structure, vectorized functions, recycling, sorting, ranking, conditionals, and extracting summaries. [Course Outline]
Fee: $279

One-Day Class Meets 8:30am-4:00pm (6.5 hours)
Code Date Location Instructor
E1541 Mon., May 3Virtual/WCMark Ratliff
E2141 Fri., Sept. 10Virtual/WCMark Ratliff

Intermediate Applications of R

(Prerequisite: Introduction to R or equivalent experience.) Build on your R analysis skills as you move into more complex data manipulation and data analysis. Learn how to manipulate, arrange, sort, merge, and summarize your data. Understand how to shape your dataset, combine data tables, and transpose data. Apply the filter function to select the appropriate data for analysis. Learn to aggregate your data and then find totals, averages, minimums, and maximums. Explore manipulating rows and columns with dplyr. Discover group processing to pull out the top three of a category or to rank items within a category, Learn to combine rows and columns, delete columns, and delete dataframes. Understand how to query your data with SQL syntax. Topics include chaining, data aggregation, summarizing data, and using the dplyr library. Additional topics include importing Excel files, ranking data, working with data relationships, merging dataframes, and working with slices or subsets of data. [Course Outline]
Fee: $279

One-Day Class Meets 8:30am-4:00pm (6.5 hours)
Code Date Location Instructor
E1542 Mon., May 10Virtual/WCMark Ratliff
E2142 Fri., Sept. 17Virtual/WCMark Ratliff

Advanced Applications of R: Level 1

(Prerequisite: Intermediate Applications of R or equivalent experience.) Explore data analysis using the more powerful tools available in R. Learn to reshape tables and go from wide to long format and back again. Understand another way to work with categories using factors to manage data that is described in words rather than numerical values. Discover the power of performing interactive data analysis by creating tabular data using factors or categorical variables. Gain insights as you look at levels when you peek under the hood of a factor. Understand dates, date formats, date arithmetic, times, and time zones pulling out date and time elements. Unlock the keys to managing your data to handle missing values, select the correct format, and ensure that your data is imported properly into R. Work with graphs and visualizations. Learn to handle more dimensions as you explore multidimensional arrays and matrices. Topics include character and string manipulation, text extraction, POSIX, and date conversion. Additional topics include specifying data type during imports, logical expressions, mixing objects, and explicit coercion. [Course Outline]
Fee: $279

One-Day Class Meets 8:30am-4:00pm (6.5 hours)
Code Date Location Instructor
E1543 Mon., May 17Virtual/WCMark Ratliff
E2143 Fri., Sept. 24Virtual/WCMark Ratliff

Advanced Applications of R: Level 2

(Prerequisite: Advanced Applications of R: Level 1 or equivalentexperience.) Understand lists and list structure, and how it adds more power to R. Work with regular expressions for text extraction to manipulate your data. Learn to write your own functions to handle special situations. Discover the apply family of functions and how they provide powerful and efficient looping mechanisms. Set up basic scripts for repeatable analysis and understand how to use control structures within the scripts. Topics include checking quartiles, finding the center of your data, describing distributions, tracking correlations, plotting densities, and creating box plots. Additional topics include working with graphics, creating different types of plots, manipulating files, and producing reports.  [Course Outline]
Fee: $279

One-Day Class Meets 8:30am-4:00pm (6.5 hours)
Code Date Location Instructor
E1544 Mon., May 24Virtual/WCMark Ratliff
E2144 Fri., Oct. 1Virtual/WCMark Ratliff

If you would like to register for a course, call (314) 984-9000 or register online.

Classes are also available in SQL (Structured Query Language) commands which can be used in a variety of client/server database systems.