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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 Trial
      Free Trial
      I

      IBM

      IBM Introduction to Machine Learning

      Skills you'll gain: Exploratory Data Analysis, Unsupervised Learning, Supervised Learning, Feature Engineering, Dimensionality Reduction, Data Cleansing, Data Access, Regression Analysis, Data Analysis, Machine Learning Algorithms, Machine Learning, Statistical Inference, Statistical Hypothesis Testing, Data Quality, Data Science, Classification And Regression Tree (CART), Scikit Learn (Machine Learning Library), Applied Machine Learning, Probability & Statistics, Predictive Modeling

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.9K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Alberta

      Fundamentals of Reinforcement Learning

      Skills you'll gain: Reinforcement Learning, Machine Learning, Machine Learning Algorithms, Artificial Intelligence, Markov Model, Algorithms, Probability Distribution

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2.8K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      S

      Stanford University

      Probabilistic Graphical Models 2: Inference

      Skills you'll gain: Bayesian Network, Bayesian Statistics, 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
      ·
      488 reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Pennsylvania

      Fundamentals of Quantitative Modeling

      Skills you'll gain: Mathematical Modeling, Statistical Modeling, Regression Analysis, Business Modeling, Financial Modeling, Business Mathematics, Markov Model, Probability, Predictive Analytics, Process Optimization, Risk Management, Statistics, Probability Distribution, Simulation and Simulation Software, Forecasting

      4.6
      Rating, 4.6 out of 5 stars
      ·
      9.1K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      D

      Duke University

      Excel to MySQL: Analytic Techniques for Business

      Skills you'll gain: Data Storytelling, Database Design, Dashboard, MySQL, Relational Databases, SQL, Tableau Software, Business Analytics, Business Metrics, Data Visualization Software, Analytics, Data Visualization, Business Process Improvement, Business Intelligence, Financial Modeling, Microsoft Excel, Business Process, Probability Distribution, Business Risk Management, Predictive Modeling

      4.6
      Rating, 4.6 out of 5 stars
      ·
      15K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Washington

      Computational Neuroscience

      Skills you'll gain: Supervised Learning, Network Model, Matlab, Machine Learning Algorithms, Artificial Neural Networks, Neurology, Computer Science, Reinforcement Learning, Computational Thinking, Mathematical Modeling, Biology, Linear Algebra, Probability & Statistics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.1K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Data Science: Statistics and Machine Learning

      Skills you'll gain: Shiny (R Package), Rmarkdown, Regression Analysis, Leaflet (Software), Exploratory Data Analysis, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Plotly, Machine Learning Algorithms, Interactive Data Visualization, Probability & Statistics, Data Visualization, Statistical Machine Learning, Feature Engineering, Statistical Analysis, Statistical Modeling, Probability, Data Science, Data Analysis

      4.4
      Rating, 4.4 out of 5 stars
      ·
      7.2K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Introduction to Data Science in Python

      Skills you'll gain: Pandas (Python Package), Jupyter, NumPy, Data Manipulation, Data Science, Data Structures, Data Analysis, Statistical Analysis, Pivot Tables And Charts, Data Cleansing, Data Import/Export, Probability & Statistics, Python Programming, Programming Principles

      4.5
      Rating, 4.5 out of 5 stars
      ·
      27K reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      Universidad de los Andes

      Fundamentos de probabilidad y aplicaciones

      Skills you'll gain: Probability, Probability Distribution, Applied Mathematics, Statistics, Risk Management, Risk Modeling, Combinatorics, Descriptive Statistics

      4.8
      Rating, 4.8 out of 5 stars
      ·
      172 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Toronto

      Introduction to Self-Driving Cars

      Skills you'll gain: Control Systems, Embedded Software, Automation, Simulation and Simulation Software, Software Architecture, Safety Assurance, Systems Architecture, Verification And Validation, Mathematical Modeling, Computer Hardware

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.9K reviews

      Advanced · Course · 1 - 3 Months

    • T

      The University of North Carolina at Chapel Hill

      Epidemiology: The Basic Science of Public Health

      Skills you'll gain: Epidemiology, Public Health and Disease Prevention, Public Health, Infectious Diseases, Research Design, Health Policy, Biostatistics, Science and Research, Health Care, Probability & Statistics, Statistical Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      4.9K reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      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, Probability & Statistics, Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      303 reviews

      Advanced · Course · 1 - 3 Months

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

    • IBM Introduction to Machine Learning: IBM
    • Fundamentals of Reinforcement Learning: University of Alberta
    • Probabilistic Graphical Models 2: Inference: Stanford University
    • Fundamentals of Quantitative Modeling: University of Pennsylvania
    • Excel to MySQL: Analytic Techniques for Business: Duke University
    • Computational Neuroscience: University of Washington
    • Data Science: Statistics and Machine Learning: Johns Hopkins University
    • Introduction to Data Science in Python: University of Michigan
    • Fundamentos de probabilidad y aplicaciones: Universidad de los Andes
    • Introduction to Self-Driving Cars: University of Toronto

    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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