Course curriculum

    1. 0.0 - Welcome Screen

    2. 0.1 - How to use the Actuartech platform

    3. 0.2 - Introducing R

    4. 0.3 - How to get set up

    5. 0.4 - A User Guide for Jupyter Notebooks

    6. 0.5 - Other ways to code in R: R Studio

    7. 0.6 - Software and package requirements

      FREE PREVIEW

    1. Introduction

      FREE PREVIEW

    2. Outline of the course

      FREE PREVIEW

    1. Video 1.1: Modelling continuous explanatory variables with Generalized additive models

    2. Slides 1.1: Modelling continuous explanatory variables with Generalized additive models

    3. Quiz 1.1

    4. Video 1.2: Penalized regression techniques (Lasso, Ridge, interaction detection, etc)

    5. Slides 1.2: Penalized regression techniques (Lasso, Ridge, interaction detection, etc.)

    6. Quiz 1.2

    1. Introduction to machine learning

    2. Supervised Machine Learning: Part 1

    3. Supervised Machine Learning: Part 2

    1. Live Lesson: Cross-validation and parameters tuning: How to calibrate a ML model in practice

    2. Slides: Cross-validation and parameters tuning: How to calibrate a ML model in practice

    3. Recording: Cross-validation and parameters tuning

    1. Example: Prediction of Number of claims with a Regression tree

    2. Hands-on Case Study: Prediction of Number of claims with a GBM

    3. Hands-on Case Study: Prediction of Number of claims with a GBM (downloadable)

    4. Hands-on Case Study: Prediction of Random Forest on Average Claim Amount

    5. Hands-on Case Study: Prediction of Random Forest on Average Claim Amount (downloadable)

About this course

  • £300.00
  • 34 lessons
  • 4 hours of video content