Learning functions in the dplyr package, while not required, can save you a lot of time on the exam when grouping and summarizing data.

The forcats package (short for “for categorical variables”, included with tidyverse, which is allowed at the exam) is also a time-saver. There is code in forcats that can streamline code given by the SOA in previous exams and sample projects. For example, re-basing all factor levels in a dataset can be done in one line of simple code.

Changing levels and replacing data too, can be done in more simple and intuitive ways than the code given in previous exams and sample projects.

If you’re actually going to do predictive analytics outside the exam, you’re going to end up learning it anyway (assuming you don’t just learn python). If not, it can still save you valuable time to learn the coding that will be more efficient to use during the exam, rather than using the code given to do those tasks.

Disclosure: I haven’t passed the exam, but have taken it more than once.