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  • 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.

Popular Probability Theory Courses and Certifications


  • N

    National Taiwan University

    商管統計資料分析三 (Analytics for Business and Management (III))

    Skills you'll gain: Logistic Regression, Statistical Programming, R Programming, Statistical Methods, Statistical Analysis, Case Studies, Model Evaluation, R (Software), Statistical Modeling, Statistical Software, Regression Analysis, Advanced Analytics, Statistical Hypothesis Testing, Probability & Statistics, Statistical Inference, Business Analytics, Estimation

    Intermediate · Course · 1 - 3 Months

  • J

    Johns Hopkins University

    Data Science Decisions in Time: Information Theory & Games

    Skills you'll gain: Game Theory, Cyber Security Strategy, Data-Driven Decision-Making, Decision Intelligence, Cybersecurity, Data Science, Algorithms, Machine Learning

    Intermediate · Course · 1 - 3 Months

  • N

    Northeastern University

    Statistical Learning for Engineering Part 1

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Regression Analysis, Applied Machine Learning, Machine Learning Methods, Statistical Modeling, Model Optimization, Machine Learning Algorithms, PyTorch (Machine Learning Library), Statistical Methods, Statistical Machine Learning, Machine Learning, Predictive Analytics, Predictive Modeling, Machine Learning Software, Statistical Programming, Model Training, Statistical Software, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning

    Intermediate · Course · 1 - 3 Months

  • N

    Northeastern University

    Statistical Learning for Engineering Part 2

    Skills you'll gain: PyTorch (Machine Learning Library), Applied Machine Learning, Unsupervised Learning, Reinforcement Learning, Supervised Learning, Machine Learning Algorithms, Machine Learning Methods, Dimensionality Reduction, Statistical Machine Learning, Machine Learning, Machine Learning Software, Convolutional Neural Networks, Artificial Neural Networks, Deep Learning, Decision Tree Learning, Autoencoders, Model Optimization

    Intermediate · Course · 1 - 3 Months

  • N

    New York University

    Fundamentals of Machine Learning in Finance

    Skills you'll gain: Supervised Learning, Machine Learning Methods, Dimensionality Reduction, Unsupervised Learning, Applied Machine Learning, Machine Learning Algorithms, Decision Tree Learning, Machine Learning, Machine Learning Software, Financial Trading, Financial Market, Reinforcement Learning, Scikit Learn (Machine Learning Library), Financial Services, Market Data, Correlation Analysis, Exploratory Data Analysis, Portfolio Management, Python Programming, Artificial Neural Networks

    3.7
    Rating, 3.7 out of 5 stars
    ·
    341 reviews

    Intermediate · Course · 1 - 4 Weeks

  • N

    New York University

    Guided Tour of Machine Learning in Finance

    Skills you'll gain: Supervised Learning, Machine Learning Methods, Model Evaluation, Applied Machine Learning, Statistical Machine Learning, Machine Learning, Statistical Methods, Artificial Neural Networks, Statistical Modeling, Predictive Modeling, Model Training, Scikit Learn (Machine Learning Library), Regression Analysis, Deep Learning, Tensorflow, Logistic Regression, Jupyter, Reinforcement Learning

    3.8
    Rating, 3.8 out of 5 stars
    ·
    681 reviews

    Intermediate · Course · 1 - 4 Weeks

  • 2

    28DIGITAL

    I/O-efficient algorithms

    Skills you'll gain: File I/O, Data Structures, Theoretical Computer Science, Algorithms, Memory Management, Graph Theory, Data Access, Performance Tuning

    4.6
    Rating, 4.6 out of 5 stars
    ·
    60 reviews

    Advanced · Course · 1 - 3 Months

  • I

    IBM

    AI Workflow: Data Analysis and Hypothesis Testing

    Skills you'll gain: Exploratory Data Analysis, Data Presentation, Probability Distribution, Statistical Hypothesis Testing, Data Visualization Software, Dashboard Creation, Dashboard, Data Analysis, Data Science, Probability & Statistics, Statistical Methods, Statistical Analysis, Jupyter, Matplotlib, Data Preprocessing, Pandas (Python Package), Statistical Inference, Statistics, Python Programming, Machine Learning

    4.3
    Rating, 4.3 out of 5 stars
    ·
    128 reviews

    Advanced · Course · 1 - 4 Weeks

  • 2

    28DIGITAL

    Approximation Algorithms

    Skills you'll gain: Algorithms, Graph Theory, Model Optimization, Applied Mathematics, Theoretical Computer Science, Combinatorics, Operations Research

    4.7
    Rating, 4.7 out of 5 stars
    ·
    33 reviews

    Intermediate · Course · 1 - 4 Weeks

  • D

    Duke University

    Data Science Math Skills

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

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

    Beginner · Course · 1 - 4 Weeks

  • I

    IBM

    AI Workflow: Feature Engineering and Bias Detection

    Skills you'll gain: Feature Engineering, Data Ethics, Unsupervised Learning, Dimensionality Reduction, Responsible AI, Text Mining, Data Preprocessing, Data Transformation, Anomaly Detection, Exploratory Data Analysis, Machine Learning, Scikit Learn (Machine Learning Library), Natural Language Processing, Data Science, Quality Assurance, Data Pipelines, Machine Learning Algorithms, Classification Algorithms, Design Thinking, Python Programming

    4.4
    Rating, 4.4 out of 5 stars
    ·
    82 reviews

    Advanced · Course · 1 - 4 Weeks

  • I

    IBM

    AI Workflow: Business Priorities and Data Ingestion

    Skills you'll gain: Design Thinking, Market Opportunities, Data Integration, Data Engineering, Data Science, Analytical Skills, Data Pipelines, Data Validation, Extract, Transform, Load, Data Processing, Workflow Management, Process Modeling, Data Cleansing, Data Quality, Data Collection, Business Priorities, NumPy, Machine Learning, Python Programming

    4.3
    Rating, 4.3 out of 5 stars
    ·
    189 reviews

    Intermediate · Course · 1 - 4 Weeks

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

  • 商管統計資料分析三 (Analytics for Business and Management (III)): National Taiwan University
  • Data Science Decisions in Time: Information Theory & Games: Johns Hopkins University
  • Statistical Learning for Engineering Part 1: Northeastern University
  • Statistical Learning for Engineering Part 2: Northeastern University
  • Fundamentals of Machine Learning in Finance: New York University
  • Guided Tour of Machine Learning in Finance: New York University
  • I/O-efficient algorithms: 28DIGITAL
  • AI Workflow: Data Analysis and Hypothesis Testing: IBM
  • Approximation Algorithms: 28DIGITAL
  • Data Science Math Skills: Duke University

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