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]

Explore the Probability Course Catalog

Status: Free
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, Financial Modeling
4.8
Rating, 4.8 out of 5 stars
1.8K reviews
Beginner · Course · 1 - 3 Months
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, Data Science, Exploratory Data Analysis, Data Analysis, Statistical Visualization
4.6
Rating, 4.6 out of 5 stars
538 reviews
Intermediate · Course · 1 - 4 Weeks
Status: Free
University of London
Probability and Statistics: To p or not to p?
Skills you'll gain: Descriptive Statistics, Probability & Statistics, Statistical Methods, Statistical Hypothesis Testing, Data-Driven Decision-Making, Statistical Modeling, Data Analysis, Probability, Statistical Visualization, Probability Distribution, Statistical Analysis, Data Presentation, Sampling (Statistics), Statistical Inference, Mathematical Modeling, Decision Tree Learning, Applied Mathematics
4.6
Rating, 4.6 out of 5 stars
1.5K reviews
Beginner · Course · 1 - 3 Months
Status: Free
Stanford University
Introduction to Statistics
Skills you'll gain: Descriptive Statistics, Statistics, Statistical Methods, Sampling (Statistics), Statistical Analysis, Data Analysis, Statistical Hypothesis Testing, Regression Analysis, Statistical Inference, Probability, Exploratory Data Analysis, Quantitative Research, Probability Distribution, Correlation Analysis
4.6
Rating, 4.6 out of 5 stars
3.9K reviews
Beginner · Course · 1 - 3 Months
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 Analysis, Statistical Software, Data Science, Descriptive Statistics
4.7
Rating, 4.7 out of 5 stars
5.7K reviews
Beginner · Course · 1 - 3 Months
University of Colorado Boulder
Probability Theory: Foundation for Data Science
Skills you'll gain: Probability, Probability & Statistics, Probability Distribution, Statistics, Bayesian Statistics, Statistical Methods, Statistical Analysis, Data Analysis
Build toward a degree
4.5
Rating, 4.5 out of 5 stars
247 reviews
Intermediate · Course · 1 - 3 Months
Google
The Power of Statistics
Skills you'll gain: Sampling (Statistics), Statistical Hypothesis Testing, Probability & Statistics, Advanced Analytics, Descriptive Statistics, Probability Distribution, Data Analysis, Analytics, Statistical Analysis, Probability, Statistical Methods, Data Science, A/B Testing, Statistics, Statistical Inference, Bayesian Statistics, Statistical Programming, Jupyter
4.8
Rating, 4.8 out of 5 stars
749 reviews
Advanced · Course · 1 - 3 Months
DeepLearning.AI
Mathematics for Machine Learning and Data Science
Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Linear Algebra, Statistical Inference, A/B Testing, Applied Mathematics, NumPy, Calculus, Dimensionality Reduction, Machine Learning, Jupyter, Python Programming, Data Transformation, Data Manipulation, Data Science
4.6
Rating, 4.6 out of 5 stars
2.6K reviews
Intermediate · Specialization · 1 - 3 Months
University of California, Santa Cruz
Bayesian Statistics
Skills you'll gain: Time Series Analysis and Forecasting, Bayesian Statistics, R Programming, Forecasting, Statistical Inference, Statistical Modeling, Technical Communication, Data Analysis, Probability, Statistical Machine Learning, Statistical Methods, Statistical Analysis, Advanced Analytics, Microsoft Excel, Markov Model, Probability Distribution, Probability & Statistics, Unsupervised Learning, Regression Analysis, Predictive Modeling
4.6
Rating, 4.6 out of 5 stars
3.5K reviews
Intermediate · Specialization · 3 - 6 Months
Johns Hopkins University
Foundations of Probability and Random Variables
Skills you'll gain: R Programming, Statistical Analysis, Combinatorics, Data Analysis, Probability, Statistics, Probability Distribution, Applied Machine Learning, Probability & Statistics, Applied Mathematics, Data Science, Computational Thinking, Artificial Intelligence and Machine Learning (AI/ML), Simulations
Intermediate · Course · 1 - 3 Months
University of Michigan
Statistics with Python
Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Modeling, Statistical Inference, Statistical Methods, Bayesian Statistics, Data Visualization, Statistics, Matplotlib, Statistical Visualization, Statistical Software, Probability & Statistics, Statistical Analysis, Jupyter, Statistical Programming, Regression Analysis, Data Visualization Software, Predictive Modeling, Exploratory Data Analysis, Data Analysis
4.6
Rating, 4.6 out of 5 stars
3.3K reviews
Beginner · Specialization · 1 - 3 Months
Johns Hopkins University
Advanced Statistics for Data Science
Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Regression Analysis, Bayesian Statistics, Statistical Analysis, Probability & Statistics, Statistical Inference, Statistical Methods, Statistical Modeling, Linear Algebra, Probability, R Programming, Biostatistics, Data Analysis, Data Science, Probability Distribution, Mathematical Modeling, Data Modeling, Applied Mathematics, Predictive Modeling
4.4
Rating, 4.4 out of 5 stars
754 reviews
Advanced · Specialization · 3 - 6 Months