Why is it important to learn 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.

What are typical careers that use probability?

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.

How can online courses on Coursera help me learn probability?

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.

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1365 résultats pour ''probability'

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IBM Skills Network
IBM Data Science
Compétences que vous acquerrez : Python Programming, Data Science, Data Analysis, Data Structures, Statistical Programming, Machine Learning, Data Mining, Regression, Machine Learning Algorithms, Data Visualization, General Statistics, Basic Descriptive Statistics, SQL, Applied Machine Learning, Statistical Analysis, Computer Programming Tools, Data Analysis Software, Machine Learning Software, Software Visualization, Databases, Programming Principles, Exploratory Data Analysis, Algebra, Data Management, Database Theory, Data Visualization Software, R Programming, Statistical Machine Learning, Statistical Tests, Deep Learning, Probability & Statistics, Statistical Visualization, Database Application, Extract, Transform, Load, Devops Tools, SPSS, Estimation, Interactive Data Visualization, Algorithms, Computer Programming, Database Administration, Geovisualization, Plot (Graphics), Reinforcement Learning, Theoretical Computer Science, Big Data, Business Analysis, Computational Logic, Correlation And Dependence, Econometrics, Entrepreneurship, Marketing, Mathematical Theory & Analysis, Mathematics, Spreadsheet Software, Storytelling, Supply Chain Systems, Supply Chain and Logistics, Writing
4.6
(105.9k avis)
Beginner · Professional Certificate · 3-6 Months
Johns Hopkins University
Advanced Statistics for Data Science
Compétences que vous acquerrez : Probability & Statistics, General Statistics, Mathematics, Probability Distribution, Regression, Linear Algebra, Bayesian Statistics, Experiment, Econometrics, Machine Learning, Basic Descriptive Statistics, Biostatistics, Calculus, Statistical Tests, Algebra, Artificial Neural Networks, Dimensionality Reduction, Machine Learning Algorithms, Statistical Machine Learning, Communication, Correlation And Dependence, Data Analysis, Estimation, Exploratory Data Analysis, Statistical Analysis
4.4
(688 avis)
Advanced · Specialization · 3-6 Months
Imperial College London
Mathematics for Machine Learning
Compétences que vous acquerrez : 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 avis)
Beginner · Specialization · 3-6 Months
Gratuit
Stanford University
Introduction to Statistics
Compétences que vous acquerrez : Data Science, General Statistics, Probability & Statistics, Statistical Tests, Estimation, Basic Descriptive Statistics, Correlation And Dependence, Probability Distribution, Regression, Bayesian Statistics, Data Analysis, Data Visualization, Econometrics, Experiment, Machine Learning, Markov Model, Plot (Graphics), Statistical Analysis, Statistical Visualization
4.5
(1.9k avis)
Beginner · Course · 1-3 Months
University of California, Santa Cruz
Bayesian Statistics
Compétences que vous acquerrez : Probability & Statistics, Bayesian Statistics, General Statistics, Probability Distribution, Data Science, Statistical Programming, R Programming, Regression, Forecasting, Machine Learning, Markov Model, Statistical Machine Learning, Bayesian Network, Basic Descriptive Statistics, Estimation, Experiment, Correlation And Dependence, Data Visualization, Machine Learning Algorithms, Statistical Tests, Statistical Visualization, Advertising, Business Analysis, Communication, Data Analysis, Graph Theory, Marketing, Mathematics, Statistical Analysis
4.6
(3.3k avis)
Intermediate · Specialization · 3-6 Months
Gratuit
Meta
Meta Social Media Marketing
Compétences que vous acquerrez : Marketing, Communication, Digital Marketing, Social Media, Advertising, Marketing Management, Marketing Design, Brand Management, Research and Design, Business Analysis, Sales, Media Strategy & Planning, Business Psychology, Marketing Psychology, Entrepreneurship, Market Research, Planning, Finance, Customer Analysis, Advertising Sales, Leadership and Management, Design and Product, Product Marketing, Budget Management, Influencing, Strategy and Operations, Media Production, Business Communication, Customer Support, Financial Management, MarTech, Market Analysis, People Analysis, Performance Management, Persona Research, Spreadsheet Software, Statistical Tests, Storytelling, Writing, Strategy, Computer Networking, Data Analysis, Data Visualization, Database Administration, Databases, Experiment, Network Security, Probability & Statistics, Public Relations, Regulations and Compliance, Security Engineering, Security Strategy, Software Engineering, Software Security, Software Testing, Supply Chain and Logistics, Visual Design
4.8
(14.2k avis)
Beginner · Professional Certificate · 3-6 Months
Gratuit

Recherches liées à probability

probability and statistics

probability theory

probability and statistics: to p or not to p?

probability theory: foundation for data science

probability & statistics for machine learning & data science

using probability distributions for real world problems in r

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En résumé, voici 10 de nos cours probability les plus populaires

An Intuitive Introduction to Probability: University of Zurich
IBM Data Science: IBM Skills Network
Advanced Statistics for Data Science: Johns Hopkins University
Mathematics for Machine Learning: Imperial College London
Introduction to Statistics: Stanford University
Probability Theory: Foundation for Data Science: University of Colorado Boulder
Bayesian Statistics: University of California, Santa Cruz
Data Science Foundations: Statistical Inference: University of Colorado Boulder
Probability and Statistics: To p or not to p?: University of London
What are the Chances? Probability and Uncertainty in Statistics: Johns Hopkins University

Questions fréquentes sur Probabilité

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.‎

Le contenu de cette FAQ a été mis à disposition à des fins d'information uniquement. Il est conseillé aux étudiants d'effectuer des recherches supplémentaires afin de s'assurer que les cours et autres qualifications suivis correspondent à leurs objectifs personnels, professionnels et financiers.