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Course Description

In this course, we provide an accelerated introduction to the core competencies of data science using R. We start with an introduction to R's computing environment and workflow for conducting complex and reproducible analyses. We introduce efficient methods for data wrangling, import/export, cleaning, and processing relevant to both industry and academic data scientists. A formal framework for data visualization is presented through a grammar of graphics common to many data science languages. We conclude with lessons on written and oral data story telling for both industry and academia. 

Learning Outcomes

Upon completion of this course, participants will be able to: 

  1. Apply their foundational understanding of how data is processed in R to write efficient, neat, and reproducible analysis scripts. 

  1. Perform data import and pre-processing of raw, messy data from a variety of sources. 

  1. Apply ‘grammar of graphics’ principles to create insightful data visualizations. 

  1. Tell a cohesive story with their data using visualization. 

Sample Careers

Target Audience 

  • Job roles/levels: e.g., mid-level managers, executives, frontline staff

  • Relevant industry sectors 

  • Expected prior knowledge or experience level

  • Prefered Language  

Note:

Required 

1. R and R-studio 

2. Quarto 

Technical Requirements

You are responsible for ensuring that your computer system meets the necessary system requirements. Use the browser check tool to ensure your browser settings are compatible and up to date (results will be displayed in a new browser window).

*Course details are subject to change.

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Enrol Now - Select a section to enrol in
Section Title
Data Wrangling and Visualization
Type
Online
Dates
May 16, 2025 to May 20, 2025
Type
In-Class Instruction
Days
Wednesday, Thursday
Time
9:30AM to 11:30AM
Dates
May 21, 2025 to May 22, 2025
Type
In-Class Instruction
Days
Friday
Time
2:00PM to 5:00PM
Dates
May 23, 2025
Schedule and Location
Contact Hours
25.0
Location
  • Guelph
Delivery Options
Blended  
Course Fee(s)
Reading List / Textbook

Suggested 

R for Data Science. 2nd Ed. By Hadley Wickham ISBN: 9781492097402 

Fundamentals of Data Visualization by Claus O. Wilke. ISBN 1492031089 

Section Notes

ACCOMMODATIONS (for External Registrants only)

On-campus accommodations are available for registrants outside of the University, using the following link:

On-Campus Accommodations: May 19-23 - INSPIRE1 (Group Code) 

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