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: Preview
University of Zurich
An Intuitive Introduction to Probability
Skills you'll gain: Probability, Probability Distribution, Probability & Statistics, Risk Management, Statistics, Descriptive Statistics, Risk Analysis, Finance
4.8
Rating, 4.8 out of 5 stars
1.9K reviews
Beginner · Course · 1 - 3 Months
Status: Free Trial
DeepLearning.AI
Probability & Statistics for Machine Learning & Data Science
Skills you'll gain: Descriptive Statistics, Statistical Hypothesis Testing, Bayesian Statistics, Probability Distribution, Probability & Statistics, Sampling (Statistics), Probability, A/B Testing, Statistics, Data Science, Statistical Analysis, Statistical Inference
4.6
Rating, 4.6 out of 5 stars
589 reviews
Intermediate · Course · 1 - 4 Weeks
Status: Free Trial
Johns Hopkins University
Foundations of Probability and Random Variables
Skills you'll gain: Probability Distribution, Combinatorics, Probability & Statistics, Statistical Analysis, Bayesian Statistics, Data Analysis, Probability, Statistical Methods, R Programming, Simulations
Intermediate · Course · 1 - 3 Months
Status: Preview
University of London
Probability and Statistics: To p or not to p?
Skills you'll gain: Statistics, Descriptive Statistics, Probability & Statistics, Statistical Hypothesis Testing, Operations Research, Probability, Statistical Methods, Data Literacy, Sampling (Statistics), Mathematical Modeling, Probability Distribution, Forecasting, Estimation, Statistical Inference, Decision Making, Financial Analysis, Simulation and Simulation Software, Risk Analysis
4.6
Rating, 4.6 out of 5 stars
1.5K reviews
Beginner · Course · 1 - 3 Months
Status: Free Trial
University of Colorado Boulder
Probability Theory: Foundation for Data Science
Skills you'll gain: Probability, Probability & Statistics, Probability Distribution, Bayesian Statistics, Statistical Methods, Correlation Analysis, Data Science, Statistical Inference, Descriptive Statistics
Build toward a degree
4.5
Rating, 4.5 out of 5 stars
254 reviews
Intermediate · Course · 1 - 3 Months
Status: Free Trial
Duke University
Introduction to Probability and Data with R
Skills you'll gain: Sampling (Statistics), Exploratory Data Analysis, R Programming, Bayesian Statistics, Data Analysis, Probability Distribution, Probability, Statistical Analysis, Quantitative Research, Statistics, Statistical Inference, Descriptive Statistics
4.7
Rating, 4.7 out of 5 stars
5.8K reviews
Beginner · Course · 1 - 3 Months

What brings you to Coursera today?

Start my career

Change my career

Grow in my current role

Explore topics outside of work

Status: Preview
Stanford University
Introduction to Statistics
Skills you'll gain: Statistics, Descriptive Statistics, Probability & Statistics, Statistical Analysis, Data Analysis, Statistical Methods, Statistical Modeling, Statistical Inference, Sampling (Statistics), Statistical Hypothesis Testing, Data Science, Regression Analysis, Exploratory Data Analysis, Probability, Probability Distribution
4.6
Rating, 4.6 out of 5 stars
4.2K reviews
Beginner · Course · 1 - 3 Months
Status: Free Trial
Stanford University
Probabilistic Graphical Models
Skills you'll gain: Bayesian Network, Statistical Modeling, Markov Model, Probability Distribution, Graph Theory, Network Model, Decision Support Systems, Data-Driven Decision-Making, Probability & Statistics, Statistical Machine Learning, Sampling (Statistics), Statistical Inference, Unsupervised Learning, Supervised Learning, Machine Learning, Machine Learning Methods, Network Analysis, Statistical Methods, Algorithms, Computational Thinking
4.6
Rating, 4.6 out of 5 stars
1.5K reviews
Advanced · Specialization · 3 - 6 Months
Status: Free Trial
DeepLearning.AI
Mathematics for Machine Learning and Data Science
Skills you'll gain: Linear Algebra, Descriptive Statistics, Statistical Hypothesis Testing, Bayesian Statistics, Probability Distribution, Probability & Statistics, Sampling (Statistics), Calculus, Applied Mathematics, Advanced Mathematics, A/B Testing, Statistics, Probability, Numerical Analysis, Mathematical Modeling, Statistical Analysis, Data Science, Machine Learning Algorithms, Dimensionality Reduction, Machine Learning
4.6
Rating, 4.6 out of 5 stars
2.8K reviews
Intermediate · Specialization · 1 - 3 Months
Status: Free Trial
University of California, Santa Cruz
Bayesian Statistics
Skills you'll gain: Bayesian Statistics, Time Series Analysis and Forecasting, R Programming, Statistical Methods, Data Presentation, Forecasting, Predictive Modeling, Statistical Inference, Statistical Modeling, Markov Model, Probability, Probability & Statistics, Statistical Machine Learning, Data Analysis, Statistical Analysis, Regression Analysis, Statistics, Unsupervised Learning, Probability Distribution, Data Science
4.6
Rating, 4.6 out of 5 stars
3.5K reviews
Intermediate · Specialization · 3 - 6 Months
Status: Free Trial
Google
The Power of Statistics
Skills you'll gain: Sampling (Statistics), Statistical Analysis, Statistics, Statistical Hypothesis Testing, Data Analysis, Statistical Programming, Statistical Inference, Descriptive Statistics, Probability Distribution, Data Science, Probability, Jupyter, Python Programming
4.8
Rating, 4.8 out of 5 stars
823 reviews
Advanced · Course · 1 - 3 Months
Status: Free Trial
Imperial College London
Mathematics for Machine Learning
Skills you'll gain: Linear Algebra, Dimensionality Reduction, NumPy, Regression Analysis, Calculus, Probability & Statistics, Integral Calculus, Machine Learning Methods, Statistical Analysis, Statistics, Advanced Mathematics, Jupyter, Machine Learning Algorithms, Data Science, Mathematical Modeling, Applied Mathematics, Geometry, Artificial Neural Networks, Python Programming, Algorithms
4.6
Rating, 4.6 out of 5 stars
15K reviews
Beginner · Specialization · 3 - 6 Months