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  • Probability Theory

Results for "probability theory"


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    U

    University of Colorado Boulder

    Probability Foundations for Data Science and AI

    Skills you'll gain: Probability, Probability & Statistics, Probability Distribution, Bayesian Statistics, Statistical Methods, Data Analysis, Statistical Inference, Statistical Analysis, Artificial Intelligence

    Build toward a degree

    4.5
    Rating, 4.5 out of 5 stars
    ·
    266 reviews

    Intermediate · Course · 1 - 3 Months

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    U

    University of Zurich

    An Intuitive Introduction to Probability

    Skills you'll gain: Probability, Probability Distribution, Probability & Statistics, Statistics, Descriptive Statistics, Applied Mathematics, Risk Analysis, Finance

    4.8
    Rating, 4.8 out of 5 stars
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    1.9K reviews

    Beginner · Course · 1 - 3 Months

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    J

    Johns Hopkins University

    Foundations of Probability and Random Variables

    Skills you'll gain: R Programming, Statistical Analysis, Combinatorics, Data Analysis, Probability, Statistics, Probability Distribution, Probability & Statistics, Bayesian Statistics, Applied Mathematics, Data Science, Artificial Intelligence and Machine Learning (AI/ML), Simulations

    Intermediate · Course · 1 - 3 Months

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    D

    DeepLearning.AI

    Probability & Statistics for Machine Learning & Data Science

    Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Statistical Inference, A/B Testing, Statistical Analysis, Statistical Machine Learning, Data Science, Exploratory Data Analysis, Statistical Visualization

    4.6
    Rating, 4.6 out of 5 stars
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    644 reviews

    Intermediate · Course · 1 - 4 Weeks

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    U

    University of Colorado Boulder

    Foundations of Probability and Statistics

    Skills you'll gain: Probability, Probability & Statistics, Estimation, Probability Distribution, Markov Model, Bayesian Statistics, Statistical Methods, Statistical Inference, Sampling (Statistics), Statistical Analysis, Statistics, Artificial Intelligence, Generative AI, Data Analysis, Data Science, Descriptive Statistics, Machine Learning Algorithms, Mathematical Theory & Analysis

    Build toward a degree

    4.4
    Rating, 4.4 out of 5 stars
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    320 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: New
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    U

    University of Pittsburgh

    Probability Theory and Regression for Predictive Analytics

    Skills you'll gain: Probability Distribution, Data Science, Probability & Statistics, Predictive Analytics, Probability, Statistical Modeling, Data Analysis, Regression Analysis, Statistical Analysis, Statistical Methods, Statistical Machine Learning, Bayesian Statistics, Statistical Inference, Feature Engineering, Applied Mathematics, Python Programming, Machine Learning, Algorithms

    Build toward a degree

    Beginner · Course · 1 - 4 Weeks

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    A

    Arizona State University

    Design of Experiments

    Skills you'll gain: Experimentation, Sample Size Determination, Research Design, Regression Analysis, Statistical Analysis, Statistical Methods, Data Analysis Software, Statistical Modeling, Design Strategies, Statistical Software, Probability & Statistics, Mathematical Modeling, Analysis, Data Transformation, Descriptive Statistics, Probability Distribution, Statistical Hypothesis Testing, Variance Analysis, Data Analysis, Quality Control

    4.7
    Rating, 4.7 out of 5 stars
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    375 reviews

    Beginner · Specialization · 3 - 6 Months

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    S

    Stanford University

    Game Theory

    Skills you'll gain: Game Theory, Strategic Decision-Making, Mathematical Modeling, Graph Theory, Bayesian Statistics, Behavioral Economics, Probability, Economics, Problem Solving, Algorithms

    4.6
    Rating, 4.6 out of 5 stars
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    4.9K reviews

    Beginner · Course · 1 - 3 Months

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    S

    Stanford University

    Probabilistic Graphical Models

    Skills you'll gain: Bayesian Network, Applied Machine Learning, Graph Theory, Machine Learning Algorithms, Probability Distribution, Network Model, Statistical Modeling, Markov Model, Decision Support Systems, Machine Learning, Probability & Statistics, Network Analysis, Statistical Inference, Sampling (Statistics), Statistical Methods, Unstructured Data, Natural Language Processing, Algorithms, Computational Thinking, Test Data

    4.6
    Rating, 4.6 out of 5 stars
    ·
    1.5K reviews

    Advanced · Specialization · 3 - 6 Months

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    D

    Duke University

    Introduction to Probability and Data with R

    Skills you'll gain: Sampling (Statistics), Exploratory Data Analysis, R (Software), Statistical Inference, Probability Distribution, Bayesian Statistics, R Programming, Data Analysis, Probability, Statistics, Statistical Analysis, Descriptive Statistics

    4.7
    Rating, 4.7 out of 5 stars
    ·
    5.8K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Preview
    Preview
    S

    Stanford University

    Introduction to Statistics

    Skills you'll gain: Descriptive Statistics, Statistics, Statistical Methods, Sampling (Statistics), Statistical Analysis, Data Analysis, Statistical Modeling, Statistical Hypothesis Testing, Regression Analysis, Statistical Inference, Probability, Exploratory Data Analysis, Quantitative Research, Probability Distribution

    4.6
    Rating, 4.6 out of 5 stars
    ·
    4.2K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Data Science Decisions in Time

    Skills you'll gain: Precision Medicine, Game Theory, Reinforcement Learning, Data-Driven Decision-Making, Clinical Trials, Bioinformatics, Data Analysis, Image Analysis, Analytics, Markov Model, Bayesian Statistics, Time Series Analysis and Forecasting, Data Science, Predictive Analytics, Strategic Decision-Making, Decision Making, Anomaly Detection, Probability Distribution, Cybersecurity, Statistical Analysis

    Intermediate · Specialization · 3 - 6 Months

Searches related to probability theory

probability theory and regression for predictive analytics
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In summary, here are 10 of our most popular probability theory courses

  • Probability Foundations for Data Science and AI: University of Colorado Boulder
  • An Intuitive Introduction to Probability: University of Zurich
  • Foundations of Probability and Random Variables: Johns Hopkins University
  • Probability & Statistics for Machine Learning & Data Science: DeepLearning.AI
  • Foundations of Probability and Statistics: University of Colorado Boulder
  • Probability Theory and Regression for Predictive Analytics: University of Pittsburgh
  • Design of Experiments: Arizona State University
  • Game Theory: Stanford University
  • Probabilistic Graphical Models: Stanford University
  • Introduction to Probability and Data with R: Duke 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.‎

Online Probability Theory courses offer a convenient and flexible way to enhance your knowledge or learn new Probability Theory skills. Choose from a wide range of Probability Theory courses offered by top universities and industry leaders tailored to various skill levels.‎

When looking to enhance your workforce's skills in Probability Theory, 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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