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    • Probability

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    1420 results for "probability"

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      University of Michigan

      Human Health Risks, Health Equity, and Environmental Justice

      Skills you'll gain: Entrepreneurship, Epidemiology, Finance, Market Research, Probability & Statistics, Research and Design, Risk Management, Software Engineering, Software Testing

      Mixed · Course · 1-4 Weeks

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      Coursera Project Network

      Machine Learning for Kyphosis Disease Classification

      Skills you'll gain: General Statistics, Machine Learning, Machine Learning Algorithms, Probability & Statistics, Regression, Data Science, Python Programming

      4.6

      (7 reviews)

      Beginner · Guided Project · Less Than 2 Hours

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      Palo Alto Networks

      Palo Alto Networks Security Operations Fundamentals

      Skills you'll gain: Strategy and Operations, Security Engineering, Computer Networking, Network Security, Operating Systems, System Security, Security Software, Epidemiology, Finance, Probability & Statistics, Risk Management, Security Strategy, Marketing, Sales, Strategy

      4.7

      (59 reviews)

      Intermediate · Course · 1-3 Months

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      Johns Hopkins University

      Advanced Linear Models for Data Science 1: Least Squares

      Skills you'll gain: Probability & Statistics, Mathematics, General Statistics, Linear Algebra, Regression, Econometrics, Experiment, Machine Learning, Algebra, Artificial Neural Networks, Dimensionality Reduction, Machine Learning Algorithms, Probability Distribution, Statistical Machine Learning, Communication

      4.4

      (177 reviews)

      Advanced · Course · 1-3 Months

    Searches related to probability

    probability and statistics
    probability & statistics for machine learning & data science
    probability and statistics: to p or not to p?
    probability theory: foundation for data science
    using probability distributions for real world problems in r
    introduction to probability and data with r
    combinatorics and probability
    an intuitive introduction to probability
    1…81828384

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

    • Human Health Risks, Health Equity, and Environmental Justice: University of Michigan
    • Machine Learning for Kyphosis Disease Classification: Coursera Project Network
    • Palo Alto Networks Security Operations Fundamentals: Palo Alto Networks
    • Advanced Linear Models for Data Science 1: Least Squares: Johns Hopkins University

    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.‎

    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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