Rapid technological advances now mean that large volumes of data processed by fast computers are available to organisations. As a result, companies are seeking greater insights from this information. This presents actuaries with increased growth opportunities to use modern data science tools and techniques to solve complex and challenging business problems.
Overview and aim
This subject is a Fellowship Applications (Module 3) subject.
The aim of the subject is to teach students how to apply a range of data skills, such as neural networks, natural language processing, unsupervised learning and optimisation techniques, together with their professional judgement, to solve a variety of complex and challenging business problems. The business problems used as examples in this subject are drawn from a wide range of industries.
Learning objectives
- Assess the impact of complex business environments on all stages of a data science projects;
- Perform data science tasks using a variety of tools and techniques to successfully solve realistic business problems; and
- Contribute to the successful implementation of data driven change in an organisation.
Subject pre-requisites
This subject has pre–requisite knowledge requirements. Knowledge of the Data Science Principles (previously known as Data Analytics Principles) subject syllabus and a basic understanding of Python, Click here for more information.
Subject requirements
Google Colab is a requirement for this subject. If you are unable to access Colab you may utilise an equivalent solution, with prior approval from the Institute. For example, there may be difficulties in China due to firewall restrictions.
To apply for use of an alternative software, please complete and submit our Application for Alternative Software Use - DSA.
Subject syllabus
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More information
The below video provides a summary of the topics to be taught in this subject.