Actuartech

0.2 - Introducing R

0.3 - How to get set up

0.4 - A User Guide for Jupyter Notebooks

0.5 - Other ways to code in R: R Studio

1.2 - Introducing the Full Data Science Pipeline

1.3 - Introduction to the Case Studies and Datasets Used

1.4 - High level Principles and Considerations

1.5 - Techniques for Visualising Data in R

1.6 - Conclusion

2.1 - Introduction

2.2 - Importing and Preliminary Analysis

2.3 - Visually Comparing Trends in Natural Disasters in Asia and the Americas

2.4 - Comparing the Frequency, Deaths, and Economic Damage by Disaster Type

2.5 - Conclusion

3.1 - Introduction

3.3 - Understanding the Effect of Lockdown Restrictions on Daily Case Numbers

3.4 - Conclusion

4.1 - Introducing Shiny

4.2 - Creating a Simple Dashboard

4.3 - Expanding to a COVID-19 Dashboard

4.4 - Complete COVID-19 Dashboard as a Zip File

4.5 - RShiny Dashboard

Week 2 On-Demand Live Lesson

R Shiny Gallery of Examples

Deploying R Shiny Dashboards

R Shiny Tutorial (provided by R Studio) [Ref 1]

Mastering Shiny [Ref 2]

dplyr Helpful Guide [Ref 3]

ggplot2 Helpful Guide [Ref 4]

Technical Actuarial Standards 100 (TAS 100): Principles for Technical Actuarial Work [Ref 5]

Reference List

Examples & Best Practice