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    • Actuarial Science

    Actuarial Science Courses Online

    Understand actuarial science for careers in insurance and finance. Study risk assessment, probability, and financial mathematics.

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    Explore the Actuarial Science Course Catalog

    • Status: Preview
      Preview
      D

      Duke University

      Data Science Math Skills

      Skills you'll gain: Probability, General Mathematics, Bayesian Statistics, Calculus, Graphing, Descriptive Statistics, Algebra, Derivatives

      4.5
      Rating, 4.5 out of 5 stars
      ·
      13K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Preview
      Preview
      Y

      Yale University

      Financial Markets

      Skills you'll gain: Financial Market, Investment Banking, Portfolio Management, Finance, Capital Markets, Financial Services, Corporate Finance, Derivatives, Investments, Financial Regulation, Risk Management, Behavioral Economics, Equities, Underwriting, Securities (Finance), Lending and Underwriting, Market Dynamics, Governance, Insurance, Environmental Social And Corporate Governance (ESG)

      4.8
      Rating, 4.8 out of 5 stars
      ·
      31K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Preview
      Preview
      T

      The Hong Kong University of Science and Technology

      Python and Statistics for Financial Analysis

      Skills you'll gain: Statistical Inference, Statistical Methods, Probability Distribution, Statistics, Risk Analysis, Probability & Statistics, Financial Trading, Regression Analysis, Statistical Analysis, Data Visualization, Financial Analysis, Financial Data, Time Series Analysis and Forecasting, Financial Modeling, Pandas (Python Package), Market Trend, Python Programming, Data Manipulation

      4.4
      Rating, 4.4 out of 5 stars
      ·
      4.5K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: New
      New
      Status: Free Trial
      Free Trial
      M

      Meta

      Meta Full-Stack Developer

      Skills you'll gain: Database Design, Version Control, Unix Commands, Restful API, HTML and CSS, Jest (JavaScript Testing Framework), Django (Web Framework), Relational Databases, Git (Version Control System), React.js, SQL, API Design, GitHub, Responsive Web Design, Database Management, Application Programming Interface (API), MySQL, Data Integrity, Object Oriented Programming (OOP), Python Programming

      4.7
      Rating, 4.7 out of 5 stars
      ·
      24K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Python for Data Science, AI & Development

      Skills you'll gain: Jupyter, Web Scraping, Python Programming, Data Collection, Object Oriented Programming (OOP), Pandas (Python Package), Programming Principles, Data Structures, NumPy, Data Processing, Data Manipulation, Application Programming Interface (API), Data Import/Export, Computer Programming, Data Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      42K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      Status: AI skills
      AI skills
      I

      IBM

      IBM Data Science

      Skills you'll gain: Data Wrangling, SQL, Unsupervised Learning, Exploratory Data Analysis, Matplotlib, Supervised Learning, Data Literacy, Relational Databases, Data Manipulation, Applied Machine Learning, Data Import/Export, Data Visualization Software, Professional Networking, Predictive Modeling, Plotly, Dashboard, Data Transformation, Generative AI, Jupyter, Data Science

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      146K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    What brings you to Coursera today?

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Data Science

      Skills you'll gain: Rmarkdown, Shiny (R Package), Exploratory Data Analysis, Statistical Inference, Statistical Hypothesis Testing, Predictive Modeling, Regression Analysis, Plot (Graphics), Knitr, Statistical Analysis, Machine Learning Algorithms, R Programming, Statistical Methods, Plotly, Data Manipulation, Statistical Visualization, Statistical Modeling, Data Science, Machine Learning, GitHub

      4.5
      Rating, 4.5 out of 5 stars
      ·
      51K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Advanced Statistics for Data Science

      Skills you'll gain: Data Visualization, Probability & Statistics, Statistical Hypothesis Testing, Data Analysis, Bayesian Statistics, Statistics, Biostatistics, Linear Algebra, Statistical Analysis, Data Science, Statistical Methods, Regression Analysis, Probability, Statistical Inference, Sampling (Statistics), Statistical Modeling, Probability Distribution, R Programming, Mathematical Modeling, Sample Size Determination

      4.4
      Rating, 4.4 out of 5 stars
      ·
      764 reviews

      Advanced · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      Status: AI skills
      AI skills
      G

      Google

      Google Data Analytics

      Skills you'll gain: Data Presentation, Data Storytelling, Data Cleansing, Data Visualization, Data Validation, Rmarkdown, Data Integrity, Interactive Data Visualization, Data Ethics, Dashboard, Ggplot2, Data Quality, Stakeholder Communications, Data Literacy, Data Visualization Software, Data Analysis, SQL, Interviewing Skills, Analytical Skills, Applicant Tracking Systems

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      172K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Data Analysis with Python

      Skills you'll gain: Data Wrangling, Exploratory Data Analysis, Data Manipulation, Data Import/Export, Data Transformation, Predictive Modeling, Data Analysis, Data Cleansing, Regression Analysis, Pandas (Python Package), Data-Driven Decision-Making, Scikit Learn (Machine Learning Library), Statistical Analysis, Supervised Learning, Machine Learning Methods, Python Programming, NumPy, Data Visualization

      4.7
      Rating, 4.7 out of 5 stars
      ·
      19K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM AI Engineering

      Skills you'll gain: Prompt Engineering, Large Language Modeling, Unsupervised Learning, PyTorch (Machine Learning Library), Keras (Neural Network Library), Supervised Learning, Applied Machine Learning, Generative AI, Deep Learning, Natural Language Processing, Reinforcement Learning, Scikit Learn (Machine Learning Library), Regression Analysis, Generative AI Agents, Artificial Neural Networks, Machine Learning Algorithms, ChatGPT, Machine Learning, Python Programming, Data Science

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      21K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Applied Data Science

      Skills you'll gain: Data Wrangling, Exploratory Data Analysis, Matplotlib, Data Manipulation, Data Import/Export, Data Visualization Software, Predictive Modeling, Plotly, Dashboard, Data Transformation, Seaborn, Data Visualization, Data Analysis, Data Cleansing, Web Scraping, Jupyter, Statistical Reporting, Data Science, Python Programming, Machine Learning

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      59K reviews

      Beginner · Specialization · 3 - 6 Months

    Actuarial Science learners also search

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    1234…645

    In summary, here are 10 of our most popular actuarial science courses

    • Data Science Math Skills: Duke University
    • Financial Markets: Yale University
    • Python and Statistics for Financial Analysis: The Hong Kong University of Science and Technology
    • Meta Full-Stack Developer: Meta
    • Python for Data Science, AI & Development: IBM
    • IBM Data Science: IBM
    • Data Science: Johns Hopkins University
    • Advanced Statistics for Data Science: Johns Hopkins University
    • Google Data Analytics: Google
    • Data Analysis with Python: IBM

    Skills you can learn in Probability And Statistics

    R Programming (19)
    Inference (16)
    Linear Regression (12)
    Statistical Analysis (12)
    Statistical Inference (11)
    Regression Analysis (10)
    Biostatistics (9)
    Bayesian (7)
    Logistic Regression (7)
    Probability Distribution (7)
    Bayesian Statistics (6)
    Medical Statistics (6)

    Frequently Asked Questions about Actuarial Science

    Begin by identifying your goal—whether you’re exploring the profession, preparing for actuarial exams (like SOA P or FM), or building skills in statistics, finance, or programming.

    • For a math-focused introduction, try An Intuitive Introduction to Probability by the University of Zurich.
    • Preparing for Exam P? Consider Probability and Statistics: To p or not to p? by University of London.
    • For foundational finance, explore Introduction to Corporate Finance by Wharton.‎

    These beginner-friendly options provide a solid foundation in the core math, finance, and analytics skills used in actuarial work:

    • An Intuitive Introduction to Probability – Helps develop the probability intuition needed for actuarial exams.
    • Data Science Math Skills – Includes linear algebra, calculus, and statistics—all core to actuarial science.
    • Business and Financial Modeling – Useful for understanding common applications for investment analysis, company valuation, and forecasting.‎
    • A course covers a specific topic—like probability, financial math, or risk modeling, like Data Science Math Skills.
    • A Specialization offers a series of structured courses for broader preparation—such as math, statistics, and data modeling relevant to actuarial exams, such as Business and Financial Modeling Specialization.
    • A Professional Certificate in actuarial science is not currently available on Coursera, but related certificates—like Google Data Analytics or IBM Data Science—can help with analytical skills that complement actuarial work.‎

    Actuarial Science courses on Coursera equip learners with key skills needed to excel in the field of actuarial science:

    • Probability and Statistics: Understand the fundamental concepts of probability and how to apply statistical methods to assess risk and uncertainty.
    • Financial Mathematics: Learn about time value of money concepts, including calculating present and future values, annuities, loans, and bonds.
    • Risk Management: Gain insights into the techniques used to manage and mitigate financial risks in insurance and finance.
    • Data Analysis: Develop proficiency in using data to predict and model potential outcomes, crucial for insurance, pensions, and finance.
    • Insurance Fundamentals: Explore the principles of various types of insurance, including life, health, property, and casualty.
    • Regulatory and Ethical Issues: Understand the regulatory landscape affecting the actuarial profession and ethical considerations in actuarial practices.
    • Exam Preparation: Prepare for professional actuarial exams with focused coursework that aligns with official actuarial exam requirements. ‎

    Coursera’s Actuarial Science courses cater to a range of learners:

    • Beginners: Some foundational knowledge in mathematics is helpful, but introductory courses are designed to start with the basics of probability and financial mathematics.
    • Intermediate Learners: Those with some background in statistics or finance can delve deeper into specific areas such as advanced risk management or actuarial modeling.
    • Advanced Students and Professionals: Experienced individuals can refine their expertise with specialized courses that enhance their analytical skills and prepare them for upper-level actuarial exams.

    These courses build from basic to advanced topics, providing a solid foundation for a career in actuarial science. ‎

    Skills acquired in Actuarial Science courses can lead to several lucrative career paths:

    • Actuary: Analyze the financial costs of risk and uncertainty, using mathematics, statistics, and financial theory to study uncertain future events, particularly those of concern to insurance and pension programs.
    • Risk Analyst: Assess and manage the risk that an organization takes on in both its daily operations and long-term planning.
    • Insurance Underwriter: Decide whether to provide insurance and under what terms by evaluating insurance applications and determining coverage amounts and premiums.
    • Financial Planner: Provide clients with strategies for managing their finances, including taxes, investments, and insurance decisions.
    • Pension and Retirement Planner: Work with pension funds, designing and evaluating pension plans and helping ensure that these plans are maintained on a sound financial basis.

    A career in actuarial science is often characterized by high job satisfaction due to the challenging nature of the work and the vital role actuaries play in business decision-making. ‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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