• For Individuals
  • For Businesses
  • For Universities
  • For Governments
Degrees
Log In
Join for Free
  • Browse
  • Probability Theory

Probability Theory Courses

Courses in Probability Theory can help you learn statistical reasoning, random variables, and probability distributions. You can build skills in hypothesis testing, regression analysis, and decision-making under uncertainty. Many courses introduce tools like R, Python, and Excel, that support analyzing data and modeling real-world phenomena. You'll explore key topics such as Bayes' theorem, expected value, and the law of large numbers, all of which are crucial for applications in fields like finance, engineering, and artificial intelligence.


More to explore:

Popular Probability Theory Courses and Certifications


  • Status: Preview
    Preview
    U

    University of Zurich

    An Intuitive Introduction to Probability

    Skills you'll gain: Probability, Probability Distribution, Probability & Statistics, Statistics, Descriptive Statistics, Applied Mathematics, Risk Analysis, Finance

    4.8
    Rating, 4.8 out of 5 stars
    ·
    1.9K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Probability & Statistics for Machine Learning & Data Science

    Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Statistical Inference, A/B Testing, Statistical Analysis, Statistical Machine Learning, Data Science, Statistical Modeling, Exploratory Data Analysis, Statistical Visualization

    4.6
    Rating, 4.6 out of 5 stars
    ·
    670 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    U

    University of Pittsburgh

    Probability Theory and Regression for Predictive Analytics

    Skills you'll gain: Probability Distribution, Data Science, Probability & Statistics, Predictive Analytics, Probability, Statistical Modeling, Data Analysis, Regression Analysis, Logistic Regression, Statistical Analysis, Statistical Methods, Statistical Machine Learning, Bayesian Statistics, Statistical Inference, Feature Engineering, Applied Mathematics, Python Programming, Machine Learning, Algorithms

    Build toward a degree

    Beginner · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Foundations of Probability and Statistics

    Skills you'll gain: Probability, Statistical Inference, Estimation, Probability & Statistics, Probability Distribution, Statistical Methods, Statistics, Markov Model, Bayesian Statistics, Data Literacy, Statistical Analysis, Sampling (Statistics), Applied Mathematics, Artificial Intelligence, Generative AI, Data Analysis, Data Science, Theoretical Computer Science, Machine Learning Algorithms, Mathematical Theory & Analysis

    Build toward a degree

    4.4
    Rating, 4.4 out of 5 stars
    ·
    329 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Foundations of Probability and Random Variables

    Skills you'll gain: R Programming, Statistical Analysis, Statistical Programming, Data Analysis, Probability, Probability Distribution, Applied Machine Learning, Probability & Statistics, Applied Mathematics, Data Science, Computational Thinking, Simulations

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Probability Foundations for Data Science and AI

    Skills you'll gain: Probability, Probability & Statistics, Probability Distribution, Bayesian Statistics, Statistical Methods, Data Analysis, Statistical Analysis, Artificial Intelligence

    Build toward a degree

    4.5
    Rating, 4.5 out of 5 stars
    ·
    275 reviews

    Intermediate · Course · 1 - 3 Months

What brings you to Coursera today?

  • Status: Preview
    Preview
    S

    Stanford University

    Game Theory

    Skills you'll gain: Game Theory, Strategic Decision-Making, Mathematical Modeling, Graph Theory, Bayesian Statistics, Behavioral Economics, Probability, Economics, Problem Solving, Algorithms

    4.6
    Rating, 4.6 out of 5 stars
    ·
    4.9K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of California San Diego

    Combinatorics and Probability

    Skills you'll gain: Combinatorics, Probability, Probability Distribution, Algorithms, Bayesian Statistics, Mathematical Modeling, Statistics, Arithmetic, Python Programming, Simulations

    4.6
    Rating, 4.6 out of 5 stars
    ·
    867 reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    S

    Stanford University

    Probabilistic Graphical Models

    Skills you'll gain: Bayesian Network, Applied Machine Learning, Graph Theory, Machine Learning Algorithms, Probability Distribution, Network Model, Statistical Modeling, Markov Model, Decision Support Systems, Machine Learning, Probability & Statistics, Network Analysis, Machine Learning Methods, Statistical Inference, Sampling (Statistics), Statistical Methods, Natural Language Processing, Algorithms, Computational Thinking

    4.6
    Rating, 4.6 out of 5 stars
    ·
    1.5K reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: Preview
    Preview
    S

    Stanford University

    Introduction to Statistics

    Skills you'll gain: Descriptive Statistics, Statistics, Statistical Methods, Sampling (Statistics), Statistical Analysis, Data Analysis, Statistical Modeling, Statistical Hypothesis Testing, Regression Analysis, Statistical Inference, Probability, Exploratory Data Analysis, Quantitative Research, Probability Distribution

    4.6
    Rating, 4.6 out of 5 stars
    ·
    4.3K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    A

    Arizona State University

    Design of Experiments

    Skills you'll gain: Experimentation, Sample Size Determination, Research Design, Regression Analysis, Statistical Analysis, Statistical Methods, Data Analysis Software, Statistical Modeling, Statistical Hypothesis Testing, Design Strategies, Sampling (Statistics), Probability & Statistics, Mathematical Modeling, Analysis, Model Evaluation, Data Transformation, Descriptive Statistics, Probability Distribution, Variance Analysis, Data Analysis

    4.7
    Rating, 4.7 out of 5 stars
    ·
    377 reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Advanced Probability and Statistical Methods

    Skills you'll gain: Regression Analysis, Statistical Hypothesis Testing, Statistical Analysis, Probability & Statistics, Statistical Methods, Probability Distribution, Data Analysis, Markov Model, Data Science, Statistics, Statistical Inference, Probability, R Programming

    Intermediate · Course · 1 - 3 Months

1234…212

In summary, here are 10 of our most popular probability theory courses

  • An Intuitive Introduction to Probability: University of Zurich
  • Probability & Statistics for Machine Learning & Data Science: DeepLearning.AI
  • Probability Theory and Regression for Predictive Analytics: University of Pittsburgh
  • Foundations of Probability and Statistics: University of Colorado Boulder
  • Foundations of Probability and Random Variables: Johns Hopkins University
  • Probability Foundations for Data Science and AI: University of Colorado Boulder
  • Game Theory: Stanford University
  • Combinatorics and Probability: University of California San Diego
  • Probabilistic Graphical Models: Stanford University
  • Introduction to Statistics: Stanford University

Frequently Asked Questions about Probability Theory

Probability theory is a branch of mathematics that deals with the analysis of random phenomena. It provides a framework for quantifying uncertainty and making informed decisions based on data. Understanding probability theory is essential because it underpins many fields, including statistics, finance, science, and artificial intelligence. By grasping the principles of probability, individuals can better analyze risks, predict outcomes, and make data-driven decisions in their personal and professional lives.‎

A background in probability theory opens doors to various career opportunities. Professionals with expertise in this area can pursue roles such as data analyst, statistician, risk manager, actuary, and quantitative researcher. These positions often require the ability to interpret data, assess risks, and develop models that predict future trends. Industries such as finance, healthcare, technology, and academia value individuals who can apply probability theory to solve complex problems and enhance decision-making processes.‎

To effectively learn probability theory, you should focus on several key skills. First, a solid understanding of basic mathematics, particularly algebra and calculus, is crucial. Familiarity with statistics is also important, as probability theory is closely related to statistical methods. Additionally, developing analytical thinking skills will help you interpret data and draw meaningful conclusions. Proficiency in programming languages like Python or R can also be beneficial, especially for practical applications in data analysis and modeling.‎

There are several excellent online courses available for those interested in probability theory. For a comprehensive introduction, consider the Probability Foundations for Data Science and AI course, which covers essential concepts and their applications in data science. Another option is the Probability Theory and Regression for Predictive Analytics course, which focuses on using probability in predictive modeling. For a broader understanding, the Foundations of Probability and Statistics Specialization offers a series of courses that build foundational knowledge in both areas.‎

Yes. You can start learning probability theory on Coursera for free in two ways:

  1. Preview the first module of many probability theory courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate in probability theory, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

Learning probability theory can be approached through a combination of structured courses, self-study, and practical application. Start by enrolling in an introductory course to build foundational knowledge. Supplement your learning with textbooks and online resources that explain key concepts. Engage in hands-on practice by working on real-world problems or projects that require the application of probability theory. Joining study groups or online forums can also enhance your understanding through discussion and collaboration with peers.‎

Typical topics covered in probability theory courses include basic probability concepts, random variables, probability distributions, expected value, and the law of large numbers. Advanced courses may explore topics such as Bayesian probability, Markov chains, and stochastic processes. Additionally, many courses integrate practical applications, demonstrating how probability theory is used in fields like data science, finance, and engineering.‎

For training and upskilling employees in probability theory, courses like Engineering Probability and Statistics Part 1 and Engineering Probability and Statistics Part 2 are excellent choices. These courses provide a practical approach to applying probability concepts in engineering contexts, making them suitable for professionals looking to enhance their analytical skills. Additionally, the Advanced Probability and Statistical Methods course offers deeper insights into statistical methods that can be beneficial for workforce development.‎

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.

Other topics to explore

Arts and Humanities
338 courses
Business
1095 courses
Computer Science
668 courses
Data Science
425 courses
Information Technology
145 courses
Health
471 courses
Math and Logic
70 courses
Personal Development
137 courses
Physical Science and Engineering
413 courses
Social Sciences
401 courses
Language Learning
150 courses

Coursera Footer

Skills

  • Artificial Intelligence (AI)
  • Cybersecurity
  • Data Analytics
  • Digital Marketing
  • English Speaking
  • Generative AI (GenAI)
  • Microsoft Excel
  • Microsoft Power BI
  • Project Management
  • Python

Certificates & Programs

  • Google Cybersecurity Certificate
  • Google Data Analytics Certificate
  • Google IT Support Certificate
  • Google Project Management Certificate
  • Google UX Design Certificate
  • IBM Data Analyst Certificate
  • IBM Data Science Certificate
  • Machine Learning Certificate
  • Microsoft Power BI Data Analyst Certificate
  • UI / UX Design Certificate

Industries & Careers

  • Business
  • Computer Science
  • Data Science
  • Education & Teaching
  • Engineering
  • Finance
  • Healthcare
  • Human Resources (HR)
  • Information Technology (IT)
  • Marketing

Career Resources

  • Career Aptitude Test
  • Examples of Strengths and Weaknesses for Job Interviews
  • High-Income Skills to Learn
  • How Does Cryptocurrency Work?
  • How to Highlight Duplicates in Google Sheets
  • How to Learn Artificial Intelligence
  • Popular Cybersecurity Certifications
  • Preparing for the PMP Certification
  • Signs You Will Get the Job After an Interview
  • What Is Artificial Intelligence?

Coursera

  • About
  • What We Offer
  • Leadership
  • Careers
  • Catalog
  • Coursera Plus
  • Professional Certificates
  • MasterTrack® Certificates
  • Degrees
  • For Enterprise
  • For Government
  • For Campus
  • Become a Partner
  • Social Impact
  • Free Courses
  • Share your Coursera learning story

Community

  • Learners
  • Partners
  • Beta Testers
  • Blog
  • The Coursera Podcast
  • Tech Blog

More

  • Press
  • Investors
  • Terms
  • Privacy
  • Help
  • Accessibility
  • Contact
  • Articles
  • Directory
  • Affiliates
  • Modern Slavery Statement
  • Do Not Sell/Share
Learn Anywhere
Download on the App Store
Get it on Google Play
Logo of Certified B Corporation
© 2025 Coursera Inc. All rights reserved.
  • Coursera Facebook
  • Coursera Linkedin
  • Coursera Twitter
  • Coursera YouTube
  • Coursera Instagram
  • Coursera TikTok