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Probability Courses

Probability courses can help you learn statistical reasoning, risk assessment, hypothesis testing, and the fundamentals of random variables. You can build skills in interpreting data distributions, calculating expected values, and applying Bayes' theorem in various contexts. Many courses introduce tools like R, Python, and Excel for data analysis, along with methods for simulating probabilistic models and visualizing outcomes.


Popular Probability 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
    ·
    675 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
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    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
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    335 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
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    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: 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: Preview
    Preview
    U

    University of London

    Probability and Statistics: To p or not to p?

    Skills you'll gain: Descriptive Statistics, Statistics, Probability & Statistics, Statistical Hypothesis Testing, Data Visualization, Data-Driven Decision-Making, Statistical Modeling, Data Analysis, Probability, Probability Distribution, Sampling (Statistics), Risk Modeling, Statistical Inference, Mathematical Modeling

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

    Beginner · Course · 1 - 3 Months

What brings you to Coursera today?

  • 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
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    278 reviews

    Intermediate · 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
    ·
    869 reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of California, Santa Cruz

    Bayesian Statistics

    Skills you'll gain: Bayesian Statistics, Time Series Analysis and Forecasting, Statistical Inference, Statistical Methods, R Programming, Forecasting, Probability & Statistics, Statistical Modeling, Technical Communication, Data Presentation, Probability, Statistics, Statistical Software, Probability Distribution, Statistical Analysis, Data Analysis, Markov Model, Model Evaluation, R (Software), Data Science

    4.6
    Rating, 4.6 out of 5 stars
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    3.5K reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    D

    Duke University

    Introduction to Probability and Data with R

    Skills you'll gain: Sampling (Statistics), Exploratory Data Analysis, R (Software), Statistical Inference, Probability Distribution, Bayesian Statistics, R Programming, Data Analysis, Probability, Statistics, Statistical Analysis, Descriptive Statistics

    4.7
    Rating, 4.7 out of 5 stars
    ·
    5.9K reviews

    Beginner · Course · 1 - 3 Months

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

    University of Pittsburgh

    Mathematical Foundations for Data Science and Analytics

    Skills you'll gain: Statistical Analysis, NumPy, Probability Distribution, Matplotlib, Statistics, Pandas (Python Package), Data Science, Probability & Statistics, Probability, Statistical Modeling, Predictive Modeling, Data Analysis, Linear Algebra, Predictive Analytics, Statistical Methods, Mathematics and Mathematical Modeling, Applied Mathematics, Python Programming, Machine Learning, Logical Reasoning

    Build toward a degree

    4.1
    Rating, 4.1 out of 5 stars
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    7 reviews

    Beginner · Specialization · 1 - 3 Months

  • Status: New
    New
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    N

    Northeastern University

    Engineering Probability and Statistics Part 1

    Skills you'll gain: Probability & Statistics, Probability Distribution, Probability, Statistical Methods, Exploratory Data Analysis, Statistical Analysis, Bayesian Statistics, Descriptive Statistics, Data Analysis, Statistical Visualization, Correlation Analysis, Reliability, Risk Modeling

    Mixed · Course · 1 - 3 Months

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

  • An Intuitive Introduction to Probability: University of Zurich
  • Probability & Statistics for Machine Learning & Data Science: DeepLearning.AI
  • Foundations of Probability and Statistics: University of Colorado Boulder
  • Foundations of Probability and Random Variables: Johns Hopkins University
  • Introduction to Statistics: Stanford University
  • Probability and Statistics: To p or not to p?: University of London
  • Probability Foundations for Data Science and AI: University of Colorado Boulder
  • Combinatorics and Probability: University of California San Diego
  • Bayesian Statistics: University of California, Santa Cruz
  • Introduction to Probability and Data with R: Duke University

Frequently Asked Questions about Probability

Probability is a branch of mathematics that deals with the likelihood of events occurring. It provides a framework for quantifying uncertainty and making informed decisions based on data. Understanding probability is crucial in various fields, including finance, healthcare, engineering, and social sciences, as it helps individuals and organizations assess risks, predict outcomes, and optimize strategies. By grasping the principles of probability, you can enhance your analytical skills and make better choices in both personal and professional contexts.‎

A background in probability can open doors to various career paths. Jobs that often require a solid understanding of probability include data analyst, statistician, risk manager, actuary, and operations researcher. Additionally, roles in finance, insurance, and healthcare frequently seek professionals who can interpret data and assess risks using probabilistic models. As industries increasingly rely on data-driven decision-making, the demand for individuals skilled in probability continues to grow.‎

To learn probability effectively, you should focus on several key skills. First, a strong foundation in basic mathematics, particularly algebra and calculus, is essential. Familiarity with statistical concepts, such as distributions, mean, variance, and standard deviation, is also important. Additionally, developing analytical thinking and problem-solving skills will help you apply probability concepts to real-world situations. Proficiency in programming languages like R or Python can further enhance your ability to analyze data and implement probabilistic models.‎

There are numerous online courses available for learning probability. Some of the best options include the Foundations of Probability and Statistics Specialization, which provides a comprehensive introduction to the subject, and the Introduction to Probability and Data with R, which focuses on practical applications using R. For those looking for advanced topics, the Advanced Probability and Statistical Methods course offers deeper insights into complex concepts.‎

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

  1. Preview the first module of many probability 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, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn probability, start by identifying your learning goals and the specific areas you want to focus on. Consider enrolling in an online course that matches your interests and skill level. Engage with the course materials, complete exercises, and participate in discussions to reinforce your understanding. Additionally, practice solving real-world problems using probability concepts to enhance your skills. Regularly reviewing and applying what you've learned will help solidify your knowledge.‎

Typical topics covered in probability courses include basic probability concepts, random variables, probability distributions, conditional probability, and the law of large numbers. Advanced courses may explore topics such as Bayesian probability, Markov chains, and statistical inference. Understanding these concepts will provide you with a solid foundation to analyze uncertainty and make data-driven decisions.‎

For training and upskilling employees, courses like the Foundations of Probability and Statistics Specialization and Engineering Probability and Statistics Part 1 are excellent choices. These courses cover essential probability concepts and their applications in various fields, making them suitable for professionals looking to enhance their analytical skills and improve decision-making in their organizations.‎

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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