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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

      Imperial College London

      Introduction to Statistics & Data Analysis in Public Health

      Skills you'll gain: Analytical Skills, Sampling (Statistics), Statistical Hypothesis Testing, Data Literacy, Data Analysis, Statistical Software, R Programming, Statistics, Public Health, Descriptive Statistics, Probability Distribution, Data Import/Export

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.5K reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of London

      Foundations of Data Science: K-Means Clustering in Python

      Skills you'll gain: Data Visualization, Matplotlib, Probability & Statistics, Data Science, Unsupervised Learning, Statistics, NumPy, Python Programming, Pandas (Python Package), Machine Learning Algorithms, Data Analysis, Descriptive Statistics, Data Manipulation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      719 reviews

      Beginner · 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, Probability & Statistics, Scatter Plots, Statistics, Microsoft Excel, Excel Formulas, Data Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      28 reviews

      Beginner · Course · 1 - 3 Months

    • D

      Duke University

      Image and Video Processing: From Mars to Hollywood with a Stop at the Hospital

      Skills you'll gain: Image Analysis, Computer Vision, Digital Communications, Computer Graphics, Visualization (Computer Graphics), Medical Imaging, Applied Mathematics, Spatial Analysis, Advanced Mathematics, Linear Algebra, Matlab, Mathematical Modeling, Algorithms, Probability Distribution

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.1K reviews

      Mixed · Course · 1 - 3 Months

    • U

      University of Michigan

      Mindware: Critical Thinking for the Information Age

      Skills you'll gain: Data Analysis, Statistics, Analytical Skills, Experimentation, Critical Thinking, Research Design, Behavioral Economics, Decision Making, Regression Analysis, Probability, Correlation Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.4K reviews

      Beginner · Course · 1 - 3 Months

    • S

      Stanford University

      Game Theory II: Advanced Applications

      Skills you'll gain: Game Theory, Bidding, Social Sciences, Resource Allocation, Political Sciences, Economics, Behavioral Economics, Mathematical Theory & Analysis, Probability & Statistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      642 reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      K

      Kennesaw State University

      Six Sigma Advanced Define and Measure Phases

      Skills you'll gain: Process Capability, Team Management, Statistical Process Controls, Exploratory Data Analysis, Six Sigma Methodology, Probability & Statistics, Process Analysis, Statistical Analysis, Lean Six Sigma, Process Mapping, Correlation Analysis, Data Analysis, Data Collection, Regression Analysis, Process Improvement, Quality Improvement, Business Process, Graphing

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.3K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      C

      Columbia University

      Introduction to Financial Engineering and Risk Management

      Skills you'll gain: Financial Market, Securities (Finance), Derivatives, Financial Systems, Actuarial Science, Mathematical Modeling, Mathematics and Mathematical Modeling, Applied Mathematics, Financial Trading, Capital Markets, Financial Services, Securities Trading, Futures Exchange, Equities, Finance, Financial Modeling, Market Liquidity, Risk Modeling, Probability, Risk Management

      4.6
      Rating, 4.6 out of 5 stars
      ·
      285 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      AI for Medical Prognosis

      Skills you'll gain: Risk Modeling, Decision Tree Learning, Predictive Modeling, Feature Engineering, Applied Machine Learning, Random Forest Algorithm, Forecasting, Machine Learning, Statistical Methods, Statistical Analysis, Probability & Statistics, Data Analysis, Regression Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      787 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      IBM

      Supervised Machine Learning: Regression

      Skills you'll gain: Supervised Learning, Regression Analysis, Predictive Modeling, Machine Learning, Statistical Modeling, Classification And Regression Tree (CART), Scikit Learn (Machine Learning Library), Feature Engineering, Statistical Analysis, Performance Metric

      4.7
      Rating, 4.7 out of 5 stars
      ·
      741 reviews

      Intermediate · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Statistics For Data Science

      Skills you'll gain: Correlation Analysis, Probability & Statistics, Statistics, Statistical Analysis, Data Analysis, Data Science, Probability Distribution, Descriptive Statistics, Statistical Inference

      3.9
      Rating, 3.9 out of 5 stars
      ·
      33 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Sports Performance Analytics

      Skills you'll gain: Forecasting, Statistical Methods, Regression Analysis, Data Cleansing, Scikit Learn (Machine Learning Library), Supervised Learning, Data Processing, Statistical Hypothesis Testing, Correlation Analysis, Predictive Analytics, Predictive Modeling, Matplotlib, Applied Machine Learning, Kinesiology, Injury Prevention, Statistical Machine Learning, Analytics, Data Analysis, Statistical Analysis, Probability & Statistics

      4.5
      Rating, 4.5 out of 5 stars
      ·
      257 reviews

      Intermediate · Specialization · 3 - 6 Months

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

    • Introduction to Statistics & Data Analysis in Public Health: Imperial College London
    • Foundations of Data Science: K-Means Clustering in Python: University of London
    • Statistics and Data Analysis with Excel, Part 1: University of Colorado Boulder
    • Image and Video Processing: From Mars to Hollywood with a Stop at the Hospital: Duke University
    • Mindware: Critical Thinking for the Information Age : University of Michigan
    • Game Theory II: Advanced Applications: Stanford University
    • Six Sigma Advanced Define and Measure Phases: Kennesaw State University
    • Introduction to Financial Engineering and Risk Management: Columbia University
    • AI for Medical Prognosis : DeepLearning.AI
    • Supervised Machine Learning: Regression: IBM

    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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