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.