Here's what we recommend

The recommended prerequisite is DS4B 101-R: Business Analysis with R.

The DS4B 102-R: Shiny Web Applications (Level 1) Course is an extension of DS4B 101-R: Business Analysis with R.

At a minimum, you should to have R and the RStudio Integrated Development Environment (IDE) setup:

  • See Section 1.3 of the DS4B 101-R course.

To fully grasp DS4B 102-R (Shiny Web Applications for Business), you will need to have exposure to:

  • dplyr for data manipulation
  • ggplot2 for visualization
  • plotly for interactive visualization
  • parsnip for machine learning (and XGBoost)
  • stringr for text
  • lubridate for time series
  • forcats for categorical data
  • rmarkdown for integrating R code into HTML documents

Each of these topics are covered in DS4B 101-R: Business Analysis with R. If you have not been exposed to these tools, it's recommended to take DS4B 101-R.

Further, the machine learning models and feature engineering code are direct extensions of Project 1 - Creating a Product Pricing Algorithm - Covered in DS4B 101-R. Therefore, taking DS4B 101-R will help you complete the data science project by taking the model built in DS4B 101-R to production in DS4B 102-R.

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