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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1420 resultados para "probability"

DeepLearning.AI
Calculus for Machine Learning and Data Science
Habilidades que obtendrás: Algorithms, Calculus, Mathematics, Theoretical Computer Science, Machine Learning, Mathematical Theory & Analysis, Machine Learning Algorithms, Artificial Neural Networks, Deep Learning, Differential Equations, Probability & Statistics, Regression, Statistical Machine Learning, Algebra, Econometrics, General Statistics, Python Programming
4.8
(71 reseñas)
Beginner · Course · 1-4 Weeks
Johns Hopkins University
Advanced Statistics for Data Science
Habilidades que obtendrás: 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
(696 reseñas)
Advanced · Specialization · 3-6 Months
University of California San Diego
Introduction to Discrete Mathematics for Computer Science
Habilidades que obtendrás: Mathematics, Graph Theory, Computer Science, Computer Programming, Python Programming, Statistical Programming, Data Science, Algebra, Theoretical Computer Science, Probability & Statistics, Algorithms, Calculus, Combinatorics, Data Analysis, Statistical Analysis, General Statistics, Mathematical Theory & Analysis, Programming Principles, Bayesian Statistics, Computational Thinking, Geometry, Applied Mathematics, Correlation And Dependence, Estimation, Probability Distribution, Computational Logic, Business Analysis, Communication, Computer Architecture, Critical Thinking, Cryptography, Data Visualization, Entrepreneurship, Leadership and Management, Machine Learning, Markov Model, Microarchitecture, Problem Solving, Research and Design, Scientific Visualization, Security Engineering, Statistical Visualization, Strategy and Operations
4.5
(3.3k reseñas)
Beginner · Specialization · 3-6 Months
IBM Skills Network
Fundamentos de Ciencia de Datos con Python y SQL
Habilidades que obtendrás: Statistical Programming, Computer Programming, Python Programming, Data Management, Databases, SQL, General Statistics, Probability & Statistics, Data Analysis, R Programming, Basic Descriptive Statistics, Probability Distribution, Regression, Web Development
4.5
(299 reseñas)
Beginner · Specialization · 3-6 Months
Google
Google Data Analytics
Habilidades que obtendrás: Data Analysis, Data Science, Statistical Programming, Business Analysis, SQL, Spreadsheet Software, Business, Data Visualization, Data Management, R Programming, Exploratory Data Analysis, Statistical Visualization, Communication, Statistical Analysis, Data Analysis Software, Business Communication, Data Structures, Data Visualization Software, Tableau Software, Big Data, Cloud Computing, Collaboration, Conflict Management, Critical Thinking, Customer Analysis, General Statistics, Leadership and Management, Plot (Graphics), Probability & Statistics, Small Data, Algorithms, Application Development, Budget Management, Computational Logic, Computer Architecture, Computer Networking, Computer Programming, Computer Programming Tools, Cryptography, Data Mining, Data Model, Database Administration, Database Design, Databases, Decision Making, Design and Product, Distributed Computing Architecture, Entrepreneurship, Extract, Transform, Load, Feature Engineering, Finance, Full-Stack Web Development, Interactive Data Visualization, Machine Learning, Mathematical Theory & Analysis, Mathematics, Network Security, Other Programming Languages, Problem Solving, Product Design, Programming Principles, Project Management, Research and Design, Security Engineering, Security Strategy, Software Engineering, Software Security, Storytelling, Theoretical Computer Science, Visual Design, Visualization (Computer Graphics), Web Development
4.8
(107.7k reseñas)
Beginner · Professional Certificate · 3-6 Months
Google
Google Project Management:
Habilidades que obtendrás: Project Management, Strategy and Operations, Leadership and Management, Communication, Collaboration, Agile Software Development, Entrepreneurship, Software Engineering, Business Communication, Scrum (Software Development), Planning, Supply Chain and Logistics, Business Psychology, Change Management, Finance, Organizational Development, Product Management, Risk Management, Budget Management, Conflict Management, Design and Product, Human Resources, Influencing, Storytelling, Writing, Application Development, Business Process Management, Culture, Estimation, Marketing, Operations Management, Operations Research, Probability & Statistics, Problem Solving, Procurement, Product Design, Public Relations, Research and Design, Sales, Software Engineering Tools, Software Testing, Statistical Tests, Strategy, Supply Chain Systems, User Experience, Vendor Management
4.8
(78.4k reseñas)
Beginner · Professional Certificate · 3-6 Months
IBM Skills Network
IBM Data Science
Habilidades que obtendrás: 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, Computer Programming, Statistical Visualization, Algebra, Data Management, Database Theory, Data Visualization Software, R Programming, Statistical Machine Learning, Statistical Tests, Deep Learning, Probability & Statistics, Extract, Transform, Load, Plot (Graphics), Devops Tools, SPSS, Estimation, Interactive Data Visualization, Algorithms, Database Application, Geovisualization, Reinforcement Learning, Theoretical Computer Science, Big Data, Business Analysis, Computational Logic, Correlation And Dependence, Database Administration, Econometrics, Entrepreneurship, Marketing, Mathematical Theory & Analysis, Mathematics, Spreadsheet Software, Storytelling, Supply Chain Systems, Supply Chain and Logistics, Writing
4.6
(108.3k reseñas)
Beginner · Professional Certificate · 3-6 Months
IBM Skills Network
IBM Data Analyst
Habilidades que obtendrás: Data Analysis, Python Programming, Data Visualization, Exploratory Data Analysis, Basic Descriptive Statistics, Data Structures, Statistical Programming, Data Science, Statistical Visualization, Plot (Graphics), Data Management, General Statistics, SQL, Databases, Business Analysis, Microsoft Excel, Spreadsheet Software, Data Mining, Statistical Analysis, Programming Principles, Probability & Statistics, Regression, Machine Learning, Algebra, Computer Programming, Data Analysis Software, Database Theory, Probability Distribution, Applied Machine Learning, Statistical Tests, Big Data, Correlation And Dependence, Data Visualization Software, Estimation, NoSQL, Geovisualization, ArcGIS, Cloud Computing, Data Warehousing, Database Application, Extract, Transform, Load, HTML and CSS, Knitr, Mathematics, Minitab, PostgreSQL, R Programming, SAS (Software), SPSS, Apache, Computational Logic, Computer Programming Tools, Database Administration, Econometrics, Interactive Data Visualization, Leadership and Management, Mathematical Theory & Analysis, Operating Systems, Professional Development, Statistical Machine Learning, System Programming, Theoretical Computer Science
4.6
(62.5k reseñas)
Beginner · Professional Certificate · 3-6 Months

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En síntesis, estos son los 10 cursos más populares probability

Calculus for Machine Learning and Data Science: DeepLearning.AI
Advanced Statistics for Data Science: Johns Hopkins University
Bayesian Statistics: From Concept to Data Analysis: University of California, Santa Cruz
Introduction to Discrete Mathematics for Computer Science: University of California San Diego
Fundamentos de Ciencia de Datos con Python y SQL: IBM Skills Network
Math behind Moneyball: University of Houston
Uncertainty and Research: Johns Hopkins University
Estadísticas para la Ciencia de Datos con Python: IBM Skills Network
Google Data Analytics: Google
Google Project Management:: Google

Preguntas frecuentes sobre Probabilidad

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.‎

Se puso a disposición este contenido de preguntas frecuentes solo con fines informativos. Se les pide a los estudiantes que realicen investigaciones adicionales para asegurarse de que los cursos y otras credenciales cumplan con sus objetivos personales, profesionales y financieros.