Launch this jobs-focused Actuarial Science degree for students who want to turn math and data studies into exciting and lucrative career opportunities.
Our interviews with over 20 Fortune 500 employers, prominent actuaries, and academics led to this program, built to address the needs of real-world employers. Namely, less focus on the highest level math courses (which tend to apply to niche roles) and more data skills for a broader knowledge base.
You can launch this Actuarial Science program by adding 5 Rize courses to your existing catalog, enabling you to market an Actuarial Science degree to prospective students in as little as one semester. Expand below to read the course descriptions.
Actuaries focus on using math and statistics to evaluate risk and make strategic decisions. This course covers a range of topics relevant to actuaries, including measurement of interest rates, interest theory, and the pricing of bonds, mortgages, annuities, and other financial instruments. This course will also fully cover all content required by the Society of Actuaries Financial Mathematics (FM) Exam and its equivalents.
Actuaries and quantitative professionals deal primarily in probabilities. This course will cover a wide range of topics and introduce you to core probability concepts needed for actuarial and quantitative work. You will be able to apply to concepts of probability to real-world scenarios. This course will also fully cover all content required by the Society of Actuaries P Exam and its equivalents.
This course focuses on team-based problem-solving in actuarial science & risk management. Students will learn the fundamentals of the R programming language, RStudio, and R Markdown, and use these tools to complete a range of projects. Projects vary, but may include bond and loan amortization, analysis of the efficient frontier and the capital asset pricing method, insurance liability & estimates of expected loss. This course culminates in a capstone project that ties together skills from throughout the Actuarial Sciences program.
In an increasingly data-driven world, everyone should be able to understand the numbers that govern our lives. Whether or not you want to work as a data analyst, being “data literate” will help you in your chosen field. In this course, you’ll learn the core concepts of inference and data analysis by working with real data. By the end of the term, you’ll be able to analyze large datasets and present your results.
This course is intended as a continuation of Foundations of Data Analytics I. In this course, you’ll learn how Data Analytics are applied within the workforce. Particular attention will be paid to the role of the Data Scientist or Analyst, machine learning and the applications of Big Data. By the end of the term, you will be able to design and execute a range of data-driven experiments.
