Handbook

This course covers the actuarial professional syllabus for data analysis including techniques for mortality, health, and insurance data used in actuarial analysis and decision-making. The course covers aspects of data analysis including exploratory data analysis, data checking and cleaning, and data visualization; classification and prediction with regression and generalized linear models; descriptive, inferential and predictive analysis and models; and statistical and machine learning including supervised and unsupervised learning. The course also covers ethical, regulatory and professional issues, and risks and risk management associated with using data and data analysis. A particular focus will be placed on communication of technical results for business applications.