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Course 1: Mathematical Foundations of Actuarial Science
Description: The purpose of this course is to develop knowledge about some basic mathematical tools and to develop the ability to assess risks from a quantitative perspective, especially to apply these tools to solve problems in actuarial science. And suppose that the students have mastered the basics of calculus, probability theory and risk management before learning this course.
Main contents and concepts: calculus; probability theory; risk management (including loss frequency; loss amount; retention amount; deductible; joint insurance and risk premium).
Lesson 2: Interest Theory, Economics, and Finance
Description: This course includes interest theory, intermediate microeconomics and macroeconomics, and the foundation of finance. Basic knowledge of calculus and probability theory is required before studying this course.
Main contents and concepts: interest theory; microeconomics; macroeconomics; financial basis.
Lesson 3: Actuarial Models on Risk (Actuarial Models)
Description: Through the study of this course, students will develop the basic knowledge of the actuarial model of random events and the application of these models in insurance and financial risks. Before you study this course, you need to be proficient in calculus, probability theory, buy SOA fake certificate, buy FSA fake certificate, how to be the Fellow of Society of Actuaries? and mathematical statistics. Participants are advised to study this course after passing Course 1 and 2.
Main content and concepts: insurance and other financial random events; survival models; population data analysis; quantitative analysis of the financial impact of random events.
Lesson 4: Actuarial Modeling
Description: This course provides an initial introduction to the basics of building models and important actuarial and statistical methods for modeling. Before learning this course, you should be familiar with the relevant content of calculus, linear algebra, probability theory, and mathematical statistics.
Main content and concepts: definition of the model; why and how to use the model; model advantages and disadvantages; deterministic and random models; model selection; input and output analysis; sensitivity test; experience and feedback of research results; regression analysis; Forecast; risk theory; reliability theory