ON DEMAND: Introduction to Machine Learning and Case Studies & Practical Machine Learning Case Study

Please note; this is an on-demand training course based on a previous event. The event times stated are therefore flexible and you are able to complete the training at a time convenient to you.

Learn by way of a practical application of data science to actuarial work.

Actuaries are increasingly looking to explore data science techniques as a way to deliver new insights, utilise new datasets and develop complex models efficiently. However, challenges remain to integrate these new techniques into the standard actuarial toolkit. A key challenge for actuaries is to understand the steps involved in a typical data science project, including how to create a robust framework for developing and reviewing advanced statistical models.

Click here to read a recent article that gives an overview of the steps in a typical data science process.

Overview

Improvements in computational power have given rise to the use of data science techniques in a wide variety of areas, including finance, driverless cars, image detection, speech recognition etc. In a world of high volume and varied datasets, data science techniques are invaluable to an insurance professional's toolkit to provide actionable insights from data.

The training delivered aimed to provide:

An overview of the impact of Data science and possible applications within the Insurance Sector.

An understanding of the main techniques of Data Science including data management, machine learning, text mining, scraping and data visualisation.

Initial insight on how to address hot business topics in different fields of the Insurance Sector by leveraging data.

The training included a walkthrough of an example application of data science to actuarial work including:

Problem Specification

Data preparation

Visualisation

Model fitting

Validation

interpretation of results

Performance of fitted data science model relative to one or two alternative models

The training was aimed actuaries or other insurance professionals working in insurance looking to learn how:

Improved data and computational capabilities can tackle insurance related business challenges with increasingly sophisticated approaches

The insurance professional looking to expand their toolkit by learning practical data science skills

Data Science can be applied in an insurance context, using practical business examples.

We also provided a high level overview of the various machine learning techniques that are used covering the key supervised and unsupervised learning methods. This included examples of how data science techniques can be applied in insurance.

Prior knowledge required:

This event looked to bring data science to life by way of this introductory course

The course assumed a good technical understanding of insurance data and products

The event was open to insurance professionals from a general and life insurance background

No previous experience using programming languages was required

The event was hosted by Actuartech: www.actuartech.com.

Access to the online training platform will be emailed to you upon registration, along with all relevant training materials and additional course information.

If you have any questions, please email info@actuartech.com or visit www.actuartech.com