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.

What are the benefits of taking an online Probability course?

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

What Probability courses are best for training and upskilling employees or the workforce?

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

Top Probability Courses - Learn Probability Online

University of Zurich

An Intuitive Introduction to Probability

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

University of London

Probability and Statistics: To p or not to p?

Skills you'll gain: Descriptive Statistics, Statistics, Probability & Statistics, Statistical Hypothesis Testing, Data-Driven Decision-Making, Data Analysis, Probability, Risk Modeling, Statistical Inference, Data Visualization Software, Mathematical Modeling

Status: Free Trial

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

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, Data Collection, Probability Distribution

Status: Free Trial

Duke University

Introduction to Probability and Data with R

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

Status: New

Status: Free Trial

Case Western Reserve University

Practical Geospatial Geostatistical Modeling

Skills you'll gain: Geostatistics, Exploratory Data Analysis, Spatial Data Analysis, Spatial Analysis, Geospatial Mapping, Geospatial Information and Technology, Descriptive Statistics, Box Plots, Statistical Methods, Statistical Modeling, R Programming, Plot (Graphics), Statistical Analysis, Rmarkdown, Probability & Statistics, Data Cleansing, Data Analysis, Regression Analysis, Correlation Analysis, Data Validation

Status: Free Trial

University of Colorado Boulder

Probability Theory: Foundation for Data Science

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

Status: Free Trial

Johns Hopkins University

Foundations of Probability and Random Variables

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

Status: New

University of Colorado Boulder

Introduction to Bayesian Statistics for Data Science

Skills you'll gain: Bayesian Statistics, Statistical Inference, Statistical Modeling, Predictive Analytics, Statistical Methods, Data Ethics, Data Science, Probability, Regression Analysis, Analytical Skills, Probability Distribution

Status: New

Macquarie University

Excel Skills for Statistics and Data Analysis: Intermediate

Skills you'll gain: Interactive Data Visualization, Pivot Tables And Charts, Statistical Inference, Microsoft Excel, Correlation Analysis, Statistics, Statistical Hypothesis Testing, Probability & Statistics, Statistical Analysis, Regression Analysis, Data Analysis, Sampling (Statistics), Descriptive Statistics, Forecasting

Status: New

Status: Free Trial

University of Michigan

Network Modeling and Analysis in Python

Skills you'll gain: Network Analysis, Network Model, Graph Theory, Analysis, Algorithms, Simulations, Unsupervised Learning, Jupyter, Probability & Statistics

Status: New

Status: Free Trial

Case Western Reserve University

Using R for Geostatistical Geospatial Modeling

Skills you'll gain: Geostatistics, Exploratory Data Analysis, Spatial Analysis, Descriptive Statistics, Box Plots, Statistical Modeling, Geospatial Information and Technology, R Programming, Plot (Graphics), Rmarkdown, Data Analysis, Data Cleansing, Statistical Methods, Statistical Analysis, Data Import/Export, Simulations

Probability Courses Online

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