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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.


Popular Probability Theory Courses and Certifications


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    S

    Shanghai Jiao Tong University

    Discrete Mathematics

    Skills you'll gain: Combinatorics, Graph Theory, Theoretical Computer Science, Mathematical Theory & Analysis, Advanced Mathematics, Network Analysis, Computational Thinking, Algorithms, Data Structures, Computer Science

    3.3
    Rating, 3.3 out of 5 stars
    ·
    202 reviews

    Intermediate · Course · 1 - 3 Months

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    G

    Georgia Institute of Technology

    Games without Chance: Combinatorial Game Theory

    Skills you'll gain: Game Theory, Combinatorics, Mathematical Theory & Analysis, Computational Logic, Mathematical Modeling

    4.3
    Rating, 4.3 out of 5 stars
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    211 reviews

    Mixed · Course · 1 - 3 Months

  • Status: Free Trial
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    Stanford University

    Probabilistic Graphical Models 2: Inference

    Skills you'll gain: Bayesian Network, Machine Learning Methods, Statistical Inference, Markov Model, Graph Theory, Sampling (Statistics), Applied Machine Learning, Statistical Methods, Probability & Statistics, Algorithms, Probability Distribution, Machine Learning Algorithms, Computational Thinking

    4.6
    Rating, 4.6 out of 5 stars
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    488 reviews

    Advanced · Course · 1 - 3 Months

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    E

    Eindhoven University of Technology

    Improving your statistical inferences

    Skills you'll gain: Statistical Inference, Scientific Methods, Statistical Hypothesis Testing, Quantitative Research, Bayesian Statistics, Statistical Analysis, Probability & Statistics, Sample Size Determination, Research, R Programming, Data Sharing

    4.9
    Rating, 4.9 out of 5 stars
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    799 reviews

    Intermediate · Course · 1 - 3 Months

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    I

    Imperial College London

    Probabilistic Deep Learning with TensorFlow 2

    Skills you'll gain: Tensorflow, Autoencoders, Generative Model Architectures, Deep Learning, Applied Machine Learning, Image Analysis, Bayesian Statistics, Probability Distribution, Unsupervised Learning, Sampling (Statistics)

    4.7
    Rating, 4.7 out of 5 stars
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    109 reviews

    Advanced · Course · 1 - 3 Months

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    É

    École Polytechnique

    Aléatoire : une introduction aux probabilités - Partie 2

    Skills you'll gain: Probability, Simulations, Advanced Mathematics, Probability & Statistics, Probability Distribution, Statistical Methods, Mathematical Theory & Analysis, Sampling (Statistics), Mathematical Modeling, Statistical Inference

    4.6
    Rating, 4.6 out of 5 stars
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    40 reviews

    Mixed · Course · 1 - 3 Months

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    J

    Johns Hopkins University

    Computational and Graphical Models in Probability

    Skills you'll gain: Network Analysis, Statistical Modeling, Bayesian Network, R (Software), R Programming, Social Network Analysis, Simulations, Graph Theory, Statistical Analysis, Probability & Statistics, Markov Model, Probability Distribution, Data Visualization, Machine Learning, Statistical Hypothesis Testing

    Intermediate · Course · 1 - 4 Weeks

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    U

    University of Leeds

    Statistical Methods

    Skills you'll gain: Exploratory Data Analysis, Statistical Methods, Statistical Modeling, R (Software), Data Collection, Statistical Inference, Probability, Data Analysis, Statistical Analysis, Probability Distribution, Simulations, Statistical Visualization, Descriptive Statistics, Sampling (Statistics), Data Visualization Software

    4.8
    Rating, 4.8 out of 5 stars
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    10 reviews

    Intermediate · Course · 1 - 4 Weeks

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    U

    University of California, Santa Cruz

    Bayesian Statistics: Techniques and Models

    Skills you'll gain: Bayesian Statistics, Statistical Modeling, Statistical Methods, Model Evaluation, Markov Model, Statistical Analysis, Regression Analysis, R Programming, Data Analysis, Probability Distribution

    4.8
    Rating, 4.8 out of 5 stars
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    495 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
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    I

    Illinois Tech

    Statistical Learning

    Skills you'll gain: Statistical Analysis, Data Analysis, Statistical Programming, Statistical Machine Learning, Statistical Modeling, Model Evaluation, Regression Analysis, Bayesian Statistics, Supervised Learning, Statistical Inference, Machine Learning, Unsupervised Learning, Predictive Modeling, Feature Engineering, Logistic Regression, Decision Tree Learning, Classification Algorithms

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
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    9 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
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    S

    Stanford University

    Probabilistic Graphical Models 3: Learning

    Skills you'll gain: Bayesian Network, Applied Machine Learning, Machine Learning Algorithms, Markov Model, Machine Learning, Statistical Modeling, Network Analysis, Probability Distribution, Statistical Methods, Algorithms

    4.6
    Rating, 4.6 out of 5 stars
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    303 reviews

    Advanced · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Statistics and Data Analysis with Excel, Part 1

    Skills you'll gain: Descriptive Statistics, Statistical Visualization, Data Transformation, Data Cleansing, Probability, Box Plots, Histogram, Probability Distribution, Scatter Plots, Microsoft Excel, Excel Formulas, Data Analysis, Bayesian Statistics

    4.5
    Rating, 4.5 out of 5 stars
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    39 reviews

    Beginner · Course · 1 - 3 Months

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

  • Discrete Mathematics: Shanghai Jiao Tong University
  • Games without Chance: Combinatorial Game Theory : Georgia Institute of Technology
  • Probabilistic Graphical Models 2: Inference: Stanford University
  • Improving your statistical inferences: Eindhoven University of Technology
  • Probabilistic Deep Learning with TensorFlow 2: Imperial College London
  • Aléatoire : une introduction aux probabilités - Partie 2: École Polytechnique
  • Computational and Graphical Models in Probability: Johns Hopkins University
  • Statistical Methods: University of Leeds
  • Bayesian Statistics: Techniques and Models: University of California, Santa Cruz
  • Statistical Learning: Illinois Tech

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