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    • Probability Theory

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    832 results for "probability theory"

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      University of Zurich

      An Intuitive Introduction to Probability

      Skills you'll gain: Probability & Statistics, Probability Distribution, General Statistics, Basic Descriptive Statistics, Bayesian Network, Bayesian Statistics, Data Analysis, Machine Learning

      4.8

      (1.5k reviews)

      Beginner · Course · 1-3 Months

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      University of Colorado Boulder

      Probability Theory: Foundation for Data Science

      Skills you'll gain: General Statistics, Probability & Statistics, Probability Distribution

      4.4

      (97 reviews)

      Intermediate · Course · 1-3 Months

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      Imperial College London

      Mathematics for Machine Learning

      Skills you'll gain: Mathematics, Algebra, Linear Algebra, Machine Learning, Python Programming, Probability & Statistics, General Statistics, Calculus, Computer Programming, Applied Mathematics, Mathematical Theory & Analysis, Statistical Programming, Algorithms, Dimensionality Reduction, Regression, Theoretical Computer Science, Basic Descriptive Statistics, Data Analysis, Probability Distribution, Artificial Neural Networks, Computer Graphic Techniques, Computer Graphics, Computer Networking, Deep Learning, Differential Equations, Experiment, Machine Learning Algorithms, Network Model

      4.6

      (13.4k reviews)

      Beginner · Specialization · 3-6 Months

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      University of Colorado Boulder

      Data Science Foundations: Statistical Inference

      Skills you'll gain: General Statistics, Probability & Statistics, Probability Distribution, Statistical Tests, Calculus, Estimation, Mathematics, Business Analysis, Differential Equations, Econometrics, Spreadsheet Software

      4.4

      (128 reviews)

      Intermediate · Specialization · 3-6 Months

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      Duke University

      Introduction to Probability and Data with R

      Skills you'll gain: General Statistics, Probability & Statistics, Probability Distribution, Statistical Tests, Data Analysis, Statistical Analysis, Correlation And Dependence, Experiment, R Programming, Basic Descriptive Statistics, Bayesian Statistics, Data Mining, Plot (Graphics), Statistical Visualization, Data Analysis Software, Data Visualization, Exploratory Data Analysis, Statistical Programming

      4.7

      (5.4k reviews)

      Beginner · Course · 1-3 Months

    • Free

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      Duke University

      Data Science Math Skills

      Skills you'll gain: Mathematics, Probability & Statistics, General Statistics, Algebra, Bayesian Statistics, Computational Logic, Data Visualization, Graph Theory, Mathematical Theory & Analysis, Plot (Graphics), Probability Distribution, Theoretical Computer Science

      4.5

      (10.9k reviews)

      Beginner · Course · 1-3 Months

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      Stanford University

      Probabilistic Graphical Models 3: Learning

      Skills you'll gain: Machine Learning, Bayesian Network, Probability & Statistics, General Statistics, Bayesian Statistics, Machine Learning Algorithms, Statistical Machine Learning, Algebra, Markov Model

      4.6

      (297 reviews)

      Advanced · Course · 1-3 Months

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      University of California San Diego

      Combinatorics and Probability

      Skills you'll gain: Data Science, Computer Science, Probability & Statistics, Mathematics, Combinatorics, Data Analysis, Statistical Analysis, General Statistics, Bayesian Statistics, Computer Programming, Python Programming, Correlation And Dependence, Estimation, Probability Distribution, Computational Thinking, Theoretical Computer Science, Business Analysis, Computational Logic, Critical Thinking, Machine Learning, Markov Model, Mathematical Theory & Analysis, Research and Design, Statistical Programming, Strategy and Operations

      4.6

      (806 reviews)

      Beginner · Course · 1-3 Months

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      Stanford University

      Probabilistic Graphical Models

      Skills you'll gain: Probability & Statistics, Machine Learning, Bayesian Network, General Statistics, Markov Model, Bayesian Statistics, Probability Distribution, Computer Architecture, Distributed Computing Architecture, Leadership and Management, Other Programming Languages, Computer Programming, Machine Learning Algorithms, Statistical Machine Learning, Applied Machine Learning, Correlation And Dependence, Behavioral Economics, Business Psychology, Data Analysis, Graph Theory, Mathematics, Algebra, Geovisualization

      4.6

      (1.5k reviews)

      Advanced · Specialization · 3-6 Months

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      Stanford University

      Probabilistic Graphical Models 1: Representation

      Skills you'll gain: Probability & Statistics, General Statistics, Machine Learning, Bayesian Network, Markov Model, Leadership and Management, Probability Distribution, Bayesian Statistics, Computer Programming, Behavioral Economics, Business Psychology, Data Analysis, Graph Theory, Machine Learning Algorithms, Mathematics, Other Programming Languages, Statistical Machine Learning

      4.6

      (1.4k reviews)

      Advanced · Course · 1-3 Months

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      New York University

      Guided Tour of Machine Learning in Finance

      Skills you'll gain: Machine Learning, Finance, Machine Learning Algorithms, Algorithms, Theoretical Computer Science, Artificial Neural Networks, Business Analysis, Data Analysis, Deep Learning, Financial Analysis, Machine Learning Software, Tensorflow, Applied Machine Learning, Statistical Machine Learning

      3.8

      (644 reviews)

      Intermediate · Course · 1-4 Weeks

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      Stanford University

      Probabilistic Graphical Models 2: Inference

      Skills you'll gain: Probability & Statistics, Bayesian Network, Machine Learning, Markov Model, Computer Architecture, Distributed Computing Architecture, Applied Machine Learning, Bayesian Statistics, Correlation And Dependence, General Statistics, Other Programming Languages, Probability Distribution, Geovisualization, Machine Learning Algorithms, Statistical Machine Learning

      4.6

      (478 reviews)

      Advanced · Course · 1-3 Months

    Searches related to probability theory

    probability theory: foundation for data science
    1234…70

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

    • An Intuitive Introduction to Probability: University of Zurich
    • Probability Theory: Foundation for Data Science: University of Colorado Boulder
    • Mathematics for Machine Learning: Imperial College London
    • Data Science Foundations: Statistical Inference: University of Colorado Boulder
    • Introduction to Probability and Data with R: Duke University
    • Data Science Math Skills: Duke University
    • Probabilistic Graphical Models 3: Learning: Stanford University
    • Combinatorics and Probability: University of California San Diego
    • Probabilistic Graphical Models: Stanford University
    • Probabilistic Graphical Models 1: Representation: Stanford University

    Frequently Asked Questions about Probability Theory

    • Probability theory is a division of the mathematics field that's focused on analyzing random or uncertain distributions and phenomena. It doesn't predict a specific outcome from the data that's offered, but it tells analysts several different potential outcomes. It does this by applying mathematical equations to predict the things that may happen as a result of the information. Probability theory offers a scientific process that can be used to make an educated guess as to the most likely outcome, or event.‎

    • It's important to learn about probability theory because it can help improve your critical thinking skills. It can also help you make better decisions and help you with taking control of potential outcomes and risks. This can be beneficial in both your professional career and in your everyday life. If you're interested in a career in science, probability theory is a vital part of scientific reasoning that you'll use frequently in your career. It's also an interesting topic to learn about and to discuss with peers.‎

    • Taking online courses on Coursera can help you learn probability theory by presenting each step of the learning process in a logical order that you can pass through from beginner-level courses through intermediate and advanced courses. If you already have an understanding of data science and advanced math skills, you move right to the courses you need to upgrade or refresh your skills. You also can take the courses at your own pace, so you're never rushed, and you can make sure you have a solid understanding of each concept before progressing to the next.‎

    • If you're a highly analytical person who enjoys mathematics, probability theory may be right for you. It's also right for you if your goal is to work in the field of data science, statistical analysis, or data manipulation. Additionally, it's a useful study area if you want to work in finance or at a high-level accounting job.‎

    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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