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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


  • S

    Sungkyunkwan University

    Machine Learning Basics

    Skills you'll gain: Machine Learning, Python Programming, Supervised Learning, Model Evaluation, Scikit Learn (Machine Learning Library), Logistic Regression, Applied Machine Learning, Regression Analysis, Classification Algorithms, Statistical Methods, Linear Algebra

    4.4
    Rating, 4.4 out of 5 stars
    ·
    92 reviews

    Mixed · Course · 1 - 4 Weeks

  • P

    Packt

    Mastering Machine Learning Algorithms using Python

    Skills you'll gain: Data Science, Unsupervised Learning, Exploratory Data Analysis, Probability & Statistics, Machine Learning Algorithms, Applied Machine Learning, Classification And Regression Tree (CART), Data Analysis, Python Programming, Random Forest Algorithm, Dimensionality Reduction, Predictive Modeling, NumPy, Regression Analysis, Statistical Analysis, Data Processing, Deep Learning, Pandas (Python Package), Data Visualization, Data Manipulation

    Intermediate · Specialization · 3 - 6 Months

  • P

    Packt

    Statistics & Mathematics for Data Science & Data Analytics

    Skills you'll gain: Statistics, Data Analysis, Statistical Analysis, Regression Analysis, Analytics, Statistical Methods, Probability, Data Science, Statistical Modeling, Data-Driven Decision-Making, Statistical Inference, Probability Distribution, Applied Machine Learning, Predictive Modeling, Model Evaluation

    4.8
    Rating, 4.8 out of 5 stars
    ·
    11 reviews

    Intermediate · Course · 1 - 3 Months

  • I

    IBM

    AI Workflow: Machine Learning, Visual Recognition and NLP

    Skills you'll gain: Model Evaluation, Tensorflow, Supervised Learning, Artificial Neural Networks, Regression Analysis, Machine Learning Methods, Applied Machine Learning, Machine Learning Algorithms, Deep Learning, Image Analysis, Machine Learning, Random Forest Algorithm, Artificial Intelligence and Machine Learning (AI/ML), Decision Tree Learning, Natural Language Processing, Scikit Learn (Machine Learning Library), Convolutional Neural Networks, Computer Vision, Data Science, Python Programming

    4.4
    Rating, 4.4 out of 5 stars
    ·
    90 reviews

    Advanced · Course · 1 - 4 Weeks

  • A

    Alberta Machine Intelligence Institute

    Data for Machine Learning

    Skills you'll gain: Feature Engineering, Data Preprocessing, Model Evaluation, Data Quality, Supervised Learning, Data Validation, Data Cleansing, Data Ethics, Applied Machine Learning, Machine Learning, Unsupervised Learning, Machine Learning Algorithms, Python Programming, Computer Programming, Linear Algebra, Statistical Analysis

    4.4
    Rating, 4.4 out of 5 stars
    ·
    98 reviews

    Intermediate · Course · 1 - 4 Weeks

  • 2

    28DIGITAL

    I/O-efficient algorithms

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

    4.6
    Rating, 4.6 out of 5 stars
    ·
    60 reviews

    Advanced · Course · 1 - 3 Months

  • N

    New York University

    Fundamentals of Machine Learning in Finance

    Skills you'll gain: Supervised Learning, Dimensionality Reduction, Unsupervised Learning, Applied Machine Learning, Decision Tree Learning, Machine Learning, Financial Trading, Reinforcement Learning, Scikit Learn (Machine Learning Library), Financial Services, Regression Analysis, 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

  • I

    IBM

    AI Workflow: Enterprise Model Deployment

    Skills you'll gain: Model Deployment, Apache Spark, Data Pipelines, MLOps (Machine Learning Operations), PySpark, IBM Cloud, Jupyter, Docker (Software), Machine Learning, Data Science, Python Programming, Scalability, Design Thinking

    4.3
    Rating, 4.3 out of 5 stars
    ·
    60 reviews

    Advanced · 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, MLOps (Machine Learning Operations), Anomaly Detection, Exploratory Data Analysis, Machine Learning Methods, Machine Learning, Model Evaluation, Natural Language Processing, Data Science, Quality Assurance, Data Pipelines, Data Visualization, Python Programming

    4.4
    Rating, 4.4 out of 5 stars
    ·
    77 reviews

    Advanced · Course · 1 - 4 Weeks

  • I

    IBM

    AI Workflow: AI in Production

    Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Cloud Deployment, Unit Testing, Docker (Software), Containerization, Kubernetes, AI Workflows, IBM Cloud, Microservices, Machine Learning, Responsible AI, Business Metrics, Natural Language Processing, Time Series Analysis and Forecasting, Data Science, Python Programming

    4.5
    Rating, 4.5 out of 5 stars
    ·
    60 reviews

    Advanced · Course · 1 - 4 Weeks

  • 2

    28DIGITAL

    Approximation Algorithms

    Skills you'll gain: Algorithms, Graph Theory, Computational Thinking, Theoretical Computer Science, Operations Research, Linear Algebra

    4.7
    Rating, 4.7 out of 5 stars
    ·
    33 reviews

    Intermediate · Course · 1 - 4 Weeks

  • S

    Sungkyunkwan University

    Machine Learning Algorithms

    Skills you'll gain: Machine Learning Algorithms, Decision Tree Learning, Classification Algorithms, Unsupervised Learning, Machine Learning, Supervised Learning, Python Programming, Algorithms, Bayesian Statistics, Probability & Statistics

    3.7
    Rating, 3.7 out of 5 stars
    ·
    9 reviews

    Mixed · Course · 1 - 4 Weeks

1…151617…52

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

  • Machine Learning Basics: Sungkyunkwan University
  • Mastering Machine Learning Algorithms using Python: Packt
  • Statistics & Mathematics for Data Science & Data Analytics: Packt
  • AI Workflow: Machine Learning, Visual Recognition and NLP: IBM
  • Data for Machine Learning: Alberta Machine Intelligence Institute
  • I/O-efficient algorithms: 28DIGITAL
  • Fundamentals of Machine Learning in Finance: New York University
  • AI Workflow: Enterprise Model Deployment: IBM
  • AI Workflow: Feature Engineering and Bias Detection: IBM
  • AI Workflow: AI in Production: IBM

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