Date/Time
Date(s) - 15/06/2021
12:00 pm - 1:00 pm
Categories
NoCA Training: R Programming for Actuaries, is being presented by Rodwel Mupamberei, FIA.
Rodwel is a qualified Actuary since 2013 and has worked in a freelance capacity for few of the large UK insurers. He has applied machine techniques using R in an insurance setting by identifying hidden patterns in data and building predictive models with the aim of providing new business insights. Rodwel is an active data science practitioner using R and Python and has presented on data science at various IFoA seminars and conferences.
The course will comprise of 5 lessons of 1 hour each on:
1. 15th June 2021, 12pm – 1pm
2. 17th June 2021, 12pm – 1pm
3. 22nd June 2021, 12pm – 1pm
4. 24th June 2021, 12pm – 1pm and
5. 29th June 2021, 12pm – 1pm.
A NoCA Training Certificate will be provided on the completion of the course. A Virtual Classroom will be provided for participants to test live programs. No prior background in R language required to attend. No software installation required.
The Course will cover the following modules:
- Loading Actuarial datasets in R
- How to ingest data into R from csv, excel and databases
- How to store data in R
- Injesting multiple files
- The R dataframe data structure
- Working with large datasets in R
- Loops and iterations for typical actuarial work
- Sub-project 1: How to ingest, view and store policy model point data in R
- Data Manipulation in R
- How to get from raw data to useful data
- Introduction to tidyverse package for data manipulation
- Merging and joining datasets
- Transforming variables
- Creating you functions in R
- Best practices for data manipulation in R
- Sub-project 2: Creating new variables and joining datasets using tidyverse
- Data Visualisation in R
- Introduction to ggplot
- How to create visualizations in R
- Common pitfalls and best practice in visualisations
- Sub-project 3: Visualisation of lapse dataset in R
- Actuarial Modelling in R for Actuaries
- Introduction to the caret library in r
- Predictive modelling in R
- Feature selection
- Introduction to machine learning in R
- Choosing the right model
- Evaluation of model performance and validation
- Sub-project 4: Modelling lapse experience in R
- Communication in R
- Introduction to R shiny
- Introduction to R dashboard
- Presenting management information using R
- Sub-project 5: Creating your very first R-shiny web application to communicate results
Bookings
Bookings are closed for this event.