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Introduction to R

R is an open-source statistics program with immense flexibility, making it a great tool to develop, practice with and utilize for all varieties of analytical roles and tasks. In this course, download the software and version updates, and familiarize yourself with the workspace to import data, summarize and perform simple analysis.

The course concludes with saving work and accessing workspaces for changes or updates.

No previous computer science or programming skills are necessary.

This course can be applied to the Data Analysis Certificate.


Brendon  Dorn, MS

Brendon Dorn, MS

Brendon is a data scientist for CBRE|ESI where he uses empirical tools and methods to provide options for clients in capital project planning, predictive maintenance and repair, and energy demand forecasting. His master’s degree is in economics. Brendon has been ... read more

Benefits and Learning Outcomes

Benefits and Learning Outcomes:

  • Experience advantages of open-source software
  • Establish good patterns for using R workspace
  • Translate your business problem into programming language
  • Effectively map unique or custom problem statements to existing R packages
  • Build a repertoire for consistent and repeatable work to save time on future projects and maximize consistency

Course Outline/Topics

This course is all about basics. No previous background in computer science or programming languages is required. The course consists of six modules:

  1. Overview, downloading, updating versions of R
  2. Workspace navigation – using code or menu drop downs
  3. Searching for/installing packages
  4. Creating or importing data (e.g., Excel spreadsheet)
  5. Summarizing and visualizing data
  6. Saving work and accessing later

To elaborate upon each module, we want to think about what is to be done and with what tools:

  1. Overview, downloading, updating versions of R
    1. CRAN and Local Mirror Explanation
    2. Overview of R
    3. Install packages to check for update(s)
  2. Workspace navigation
    1. Enter basic commands
    2. Select from menu and note command that appears
    3. Interpret and fix errors
  3. Searching for/installing packages
    1. Access user-written packages
    2. Update packages in workspace
    3. Familiarize with packages needed for certain tasks
  4. Creating or importing data
    1. Create data frame – row x column table
    2. Import Excel data into R
    3. Saving data frames and tables in R workspace
  5. Summarizing and visualizing data
    1. Calculate basic summary statistics like average and variance
    2. Visualize raw data or summary statistics
  6. Saving current work and accessing previous work
    1. Differences in saving workspace, files or objects
    2. Use R markdown to track all code used
    3. Recall saved work to make changes


"This was my first real exposure to R and I really enjoyed the class. Brendon was very knowledgeable and helpful."  —  Program and Policy Analyst-Adv, 2018

All sessions are Face-to-Face unless otherwise noted.

Date: Tue-Wed, Mar 3-4

Time: 8:30am-4:30pm

Location: UWM School of Continuing Education

Instructor: Brendon Dorn MS

Fee: $895

CEUs: 1.4

Enrollment Limit: 20

Program Number: 5027-12013

Registration Deadline: Tue., Mar. 3

Registration is Closed.