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 .

Best Probability Courses & Certificates [2025]

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 Visualization, Data-Driven Decision-Making, Statistical Modeling, Data Analysis, Probability, Probability Distribution, Sampling (Statistics), Risk Modeling, Statistical Inference, 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

Google

Google Prompting Essentials

Skills you'll gain: Data Visualization, Prompt Engineering, Data Presentation, Data Storytelling, Sampling (Statistics), Presentations, Graphing, Generative AI Agents, ChatGPT, Data Ethics, AI Personalization, Generative AI, Brainstorming, Timelines, Excel Formulas, Data Analysis, Taking Meeting Minutes, Concision, Oral Expression, Artificial Intelligence

Status: Free Trial

University of Colorado Boulder

Probability Theory: Foundation for Data Science

Skills you'll gain: Probability, Probability & Statistics, Probability Distribution, Bayesian Statistics, Sampling (Statistics), Statistical Analysis, Descriptive Statistics, Statistical Inference, Correlation Analysis

Status: New

Packt

Statistics & Mathematics for Data Science & Data Analytics

Skills you'll gain: Descriptive Statistics, Probability & Statistics, Statistical Hypothesis Testing, Statistics, Data Analysis, Statistical Analysis, Regression Analysis, Analytics, Statistical Methods, Probability, Data Science, Statistical Modeling, Data-Driven Decision-Making, Statistical Inference, Probability Distribution, Predictive Analytics, Applied Machine Learning, Correlation Analysis

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

Packt

Natural Language Processing - Probability Models in Python

Skills you'll gain: Natural Language Processing, Text Mining, Scikit Learn (Machine Learning Library), Dimensionality Reduction, Statistical Machine Learning, Unsupervised Learning, Python Programming, Bayesian Statistics, NumPy, Supervised Learning, Machine Learning

Status: New

Packt

NumPy, Matplotlib & Pandas – Data Science Prerequisites

Skills you'll gain: Matplotlib, Pandas (Python Package), NumPy, Data Visualization Software, Scatter Plots, Data Manipulation, Scikit Learn (Machine Learning Library), Data Science, Statistical Methods, Data Analysis Software, Python Programming, Machine Learning, Probability Distribution, Classification And Regression Tree (CART), Linear Algebra

Probability Courses Online

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