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    • Probability

    Probability Courses Online

    Master probability theory for statistical analysis. Learn about probability distributions, expected value, and stochastic processes.

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    Explore the Probability Course Catalog

    • Status: Free
      Free
      U

      University of Zurich

      An Intuitive Introduction to Probability

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

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

      Beginner · Course · 1 - 3 Months

    • Status: Free
      Free
      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

    • 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, Exploratory Data Analysis, Statistical Visualization

      4.6
      Rating, 4.6 out of 5 stars
      ·
      563 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free
      Free
      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, Data Collection, Probability Distribution

      4.6
      Rating, 4.6 out of 5 stars
      ·
      4.1K reviews

      Beginner · Course · 1 - 3 Months

    • D

      Duke University

      Introduction to Probability and Data with R

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

      4.7
      Rating, 4.7 out of 5 stars
      ·
      5.8K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Colorado Boulder

      Probability Theory: Foundation for Data Science

      Skills you'll gain: Probability, Probability & Statistics, Probability Distribution, Bayesian Statistics, Sampling (Statistics), Statistical Analysis, Descriptive Statistics, Statistical Inference, Correlation Analysis

      Build toward a degree

      4.5
      Rating, 4.5 out of 5 stars
      ·
      253 reviews

      Intermediate · Course · 1 - 3 Months

    What brings you to Coursera today?

    • J

      Johns Hopkins University

      Foundations of Probability and Random Variables

      Skills you'll gain: R Programming, Statistical Analysis, Statistical Methods, Combinatorics, Data Analysis, Probability, Probability Distribution, Probability & Statistics, Bayesian Statistics, Applied Mathematics, Data Science, Computational Thinking, Artificial Intelligence and Machine Learning (AI/ML), Simulations

      Intermediate · Course · 1 - 3 Months

    • D

      DeepLearning.AI

      Mathematics for Machine Learning and Data Science

      Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Linear Algebra, Statistical Inference, Applied Mathematics, NumPy, Calculus, Dimensionality Reduction, Numerical Analysis, Mathematical Modeling, Machine Learning, Machine Learning Methods, Python Programming, Jupyter, Data Manipulation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.7K reviews

      Intermediate · Specialization · 1 - 3 Months

    • S

      Stanford University

      Probabilistic Graphical Models

      Skills you'll gain: Bayesian Network, Applied Machine Learning, Graph Theory, Machine Learning Algorithms, Probability Distribution, Statistical Modeling, Bayesian Statistics, Markov Model, Decision Support Systems, Machine Learning, Probability & Statistics, Network Analysis, 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

    • U

      University of California, Santa Cruz

      Bayesian Statistics

      Skills you'll gain: Time Series Analysis and Forecasting, Bayesian Statistics, R Programming, Forecasting, Statistical Inference, Statistical Modeling, Technical Communication, Data Analysis, Probability, Statistical Machine Learning, Statistical Methods, Statistical Analysis, Advanced Analytics, Mathematical Modeling, Microsoft Excel, Markov Model, Probability Distribution, Probability & Statistics, Unsupervised Learning, Regression Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.5K reviews

      Intermediate · Specialization · 3 - 6 Months

    • J

      Johns Hopkins University

      Advanced Statistics for Data Science

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

      4.4
      Rating, 4.4 out of 5 stars
      ·
      761 reviews

      Advanced · Specialization · 3 - 6 Months

    • G

      Google

      The Power of Statistics

      Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Descriptive Statistics, Data Analysis, Statistical Analysis, Probability Distribution, Statistical Methods, Advanced Analytics, Analytics, Statistics, Data Literacy, Statistical Inference, Probability, Statistical Software, Statistical Programming, A/B Testing, Sample Size Determination, Jupyter, Technical Communication

      4.8
      Rating, 4.8 out of 5 stars
      ·
      782 reviews

      Advanced · 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 and Statistics: To p or not to p?: University of London
    • Probability & Statistics for Machine Learning & Data Science: DeepLearning.AI
    • Introduction to Statistics: Stanford University
    • Introduction to Probability and Data with R: Duke University
    • Probability Theory: Foundation for Data Science: University of Colorado Boulder
    • Foundations of Probability and Random Variables: Johns Hopkins University
    • Mathematics for Machine Learning and Data Science: DeepLearning.AI
    • Probabilistic Graphical Models: Stanford University
    • Bayesian Statistics: University of California, Santa Cruz

    Frequently Asked Questions about Probability

    It's important to learn about probability if you are interested in gambling, statistics, advanced mathematics, or data science. Probability is the understanding of the likelihood of something happening, so it is part of many careers that use data analysis or planning. It is a key part of financial analysis, statistical analysis, social sciences, and medical research. Many topics that cover probability are in computer science, but not all are. Understanding probability can help you solve the data problems faced in your organization. It can also help you understand why things happen in the world.‎

    Typical careers that use probability are those that involve numbers. Probability can help a manager build a strategic plan, a scientist understand research findings, or a politician understand polling data. Some aspects of the study of probability are of use to almost anyone who has a basic understanding of math, while others are deeply theoretical. Those working in machine learning, data science, or statistical analysis will need a deep understanding of probability. When you learn probability, you will be able to understand what sets of numbers show. This is useful in analysis, exploratory data analysis, or for building probabilistic models. It is also a part of many games, so it can be useful outside of your career.‎

    Online courses on Coursera can help you learn probability no matter your current level of math skills. Some cover an intuitive approach for beginners, while others look at statistical theories. There are classes that use specific computer languages or that apply to specific industries. For example, someone working in the social sciences may want to take different courses than someone working in machine learning. Courses include lectures, readings, and projects so that you can apply what you learn. You will have the opportunity to use data sets and to apply your learning to what you see at work or at school. Some courses stand alone, and others are part of Specializations and Professional Certificates.‎

    Online Probability courses offer a convenient and flexible way to enhance your knowledge or learn new Probability skills. Choose from a wide range of Probability courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Probability, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    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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