Foundations in R for Actuaries (R1)

Learn the fundamentals of R through interactive Jupyter Notebooks, discover data management tools & techniques, statistical packages, and explore regression analysis, building your first model, validation, and visualisation.

Introduction

If you’re looking to learn the foundations of R, this course is the ideal place to start. An individual subscription gives you 3 months’ online access to:

  • Course materials
  • A personal coding environment through Jupyter Notebooks
  • Discussion forums to engage and collaborate with like-minded individuals
  • Instructional videos
  • Option to ask tutors questions through forums and Q&A sessions
  • Hands-on practical examples linked to actuarial work
  • Practical coding challenges
  • On demand access

As Well As

Our Data Science Resource Library which features Actuartech and Industry specific curated additional content to assist you on your data science journey.

You can also request to do the online assignment for an additional fee; and if successful a course completion certificate could be issued.

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Pick from any of our introductory or advanced courses with bespoke insurance and actuarial specific case studies.

Our platform is easy to use and embeds the coding environment and learning material in one place to enable you to apply data science hands-on.

We provide case studies and projects relevant to actuarial work, and based on relevant datasets provided. You have the option to interact and network with your peers.

Overview

“Foundations in R for Actuaries” introduces students to the data science pipeline whilst teaching them the fundamentals of the open source programming language, R.

Throughout this course, students are exposed to data science topics such as data cleaning, data processing, model building, and visualisation, as well as ethical and wider business considerations when using data science in practice.

This course is presented through our training platform and uses Jupyter notebooks, with the code and explanations embedded, to facilitate interactive coding. This allows you to run the code and make your own tweaks to see how it affects the output.

In this course, we consider training and testing Generalised Linear Models (GLM), and validate the results, as this is easily facilitated by R. R has robust statistical capabilities allowing users to easily fit a range of models from standard GLM’s through to neural networks.

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Foundations in R for Actuaries

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£180 once off with assignment (3-month access)

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Course Structure

Chapter 1 introduces Problem Specification, beginning with an overview of R. It highlights its ease and functionality through using R as a calculator and implementing a simple linear regression model and plotting it.

Chapter 2 covers Data Collection which addresses importing external data and how to use different data structures.

Chapter 3 on Data Management showcases how to write purpose-built functions to manage data, and transform and manipulate a dataset in preparation for model fitting.

Chapter 4 outlines Model Building using GLMs and show cases some of R’s statistical functionalities.

Chapter 5 on Visualisation shows students how to use a variety of statistical functions to produce some basic graphs which assists in understanding the data better and validating the models.

The Appendix contains additional reading and references to some of the packages discussed, as well as an additional guide for RStudio.

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Who's this course suitable for?

  • Individuals and teams who wish to learn R from the ground up.
  • Individuals and teams who wish to understand how data science can enhance their operations.
  • Individuals and teams who wish to analyse data effectively and perform robust data analytics.
  • Individuals and teams with some experience in R outside the data science and/or actuarial business context and want to see how R can be applied there.

Why is this topic important?

  • R has various actuarial applications, including experience analysis, pricing, and reserving.
  • It has many statistical and data science applications, making it capable of training and validating machine learning models.
  • R code is simple to run and is usable across a variety of system configurations.

Short note to say really enjoyed today’s webinar. It had a very clear message. […] fully in agreement with the comments that it is imperative we maintain our professional and ethical stance at all times if we want to continue to be trusted and relied on.

Webinars

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Short note to say really enjoyed today’s webinar. It had a very clear message. […] fully in agreement with the comments that it is imperative we maintain our professional and ethical stance at all times if we want to continue to be trusted and relied on.

Webinars

I just wanted to say what an interesting presentation that was. Thank you so much for taking the time to put this on for us, it is very much appreciated by all – especially the flexibility around hosting as a webinar instead of the original [in-person] format. It worked very well indeed!

Webinars

I think I’m [one of the first actuaries in my area] who are pointing towards Data Science, creating the new [role] of Actuarial data Scientist. For this reason i [sic] decided to follow a post graduate master in Business Intelligence and Big data analytics. I'm actively following your company and i [sic] think it is one of the best Actuarial consulting company [sic] who [sic] is pointing towards data Science!

Webinars

I love your videos - being free and accessible really helped me. The Q&A session was fantastic! It always comes down to execution and I feel this should always accompany your presentations - answering the question of how will your participants use what you give them. Keep up the great work!

Round Table

Thank you for having me along. I really found it the most motivating conversation I’ve had in a while, and made me think about what I’m trying to achieve within this area. We all need evenings like that to get some perspective on what we *think* is going on and what actually is. It was a very good evening.

Round Table

It was a really good introduction to Data Science and afterwards I felt that I now have a platform that I could use to further my understanding in this area.

Webinars

I am really happy to have been part of the talk. It was very insightful and please keep doing more of this. I am a data science student currently but I have an actuarial background. I worked in life insurance for about 5 months before resigning to do my masters in Data science so that I blend the actuarial world and Data science together. The talk gave me perspective. Even suggested some potential topics for my Thesis.

Webinars
Get started

Foundations in R for Actuaries

Sign up for a free preview of this introductory course in R

Free Preview

Preview

£180 once off with assignment (3-month access)

Enroll Today

£150 once-off without assignment (3-month access)

Enroll Today

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