In this visual data analysis with R course, you will learn to use visualizations such as histograms, scatter plots, and box plots to perform exploratory data analysis (EDA).
Although most people are familiar with data visualization in the context of business intelligence dashboards, this is only the tip of the iceberg. In this hands-on course, you will learn to use visualizations the way data scientists use them—to get to the “why” of what’s going on in the business.
In this course, you will learn to use visualizations such as histograms, scatter plots, and box plots to perform exploratory data analysis (EDA). EDA is not only a fundamental skill for data analysts/scientists, it’s also a fundamental skill for any data-literate professional.
You will learn to use data visualizations to find patterns in data that provide insights into business questions such as:
- Does paid conversion vary by age?
- How does component mix influence product lifespan?
- What are the trends in our sales over the past X years?
- Given the data, could we build a useful machine learning model?
Via a series of hands-on labs, you will craft powerful data visualizations using the ggplot2 library in R. This course is designed for a broad audience, and no prior knowledge of R programming is required.
The goal of this course is for you to return to work and start employing these techniques to analyze your own data.
Want to know the best part?
Although the course uses R because it is free, all the concepts/techniques you will learn are applicable to any tool you might use—even Microsoft Excel!
You Will Learn
- How to frame your analysis in terms of business questions
- How visualizations can be used to analyze data and get to the “why”
- Visual analysis techniques for numerical and categorical data
- Visual analysis techniques for data over time
- How to create data visualizations in R using ggplot2
- How to increase the power of your visual data analyses by adding dimensions
- Additional resources to extend your learning
- Business/data analysts
- Database developers
- BI/report developers
- Anyone interested in visual data analysis
No skills in programming or statistics are required!
- Windows or Mac OS X
- 64-bit operating system
- 8 MB of available RAM
- 1 GB available on hard drive to download and install R, RStudio, and ggplot2
Instructions will be emailed to registrants prior to the event to prepare your laptop BEFORE the conference. There is no time allotted in class for laptop preparation.