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.