What is discrete mathematics?

Discrete mathematics refers to a group of mathematics branches that deal with discrete objects instead of continuous objects. In discrete mathematics, objects have distinct, separate values represented by integers, unlike real numbers used in continuous mathematics. Discrete mathematics includes combinatorics, set theory, graph theory, number theory, and probability. It is integral to computer science and plays a role in the field of data science.

Why learn discrete mathematics?

You may consider learning discrete mathematics if you want to study computer science or work in a data science field. Discrete mathematics is a foundation of computer science, and programmers often use principles of set theory, probability, and combinations to analyze algorithms when writing programs and applications. Learning discrete mathematics can also help boost other useful skills like logic, reasoning, and problem-solving, making you a more marketable job candidate.

What are typical careers that use discrete mathematics?

Typical careers that use discrete mathematics are in the computer science field, such as software development, programming, and cryptography. Data scientists and data analysts may use their knowledge of discrete mathematics in their work. Other careers that can incorporate discrete mathematics include electrical and mechanical engineers in addition to data analysts, business analysts, and market researchers. Discrete mathematics also influences the work of urban planners, epidemiologists, and social scientists who collect and analyze large amounts of data.

How can online courses help me learn discrete mathematics?

Online courses can introduce you to core concepts of discrete mathematics, such as sets, relations, and functions. Lessons include topics like partial orders, enumerative combinatorics, and the binomial coefficient, and you have opportunities to apply the concepts to real-world applications. You may choose courses that cover specific subjects like graph theory or probability to increase your knowledge of these disciplines. Alternatively, you may decide to take courses that explore the application of discrete mathematics in specific fields like data science, computer science, or machine learning.

What are the benefits of taking an online Discrete Mathematics course?

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

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

When looking to enhance your workforce's skills in Discrete Math, 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 Discrete Mathematics Courses & Certificates [2025]

Explore the Discrete Mathematics Course Catalog

Status: Free Trial
University of California San Diego
Introduction to Discrete Mathematics for Computer Science
Skills you'll gain: Graph Theory, Combinatorics, Computational Logic, Computational Thinking, Probability, Theoretical Computer Science, Logical Reasoning, Deductive Reasoning, Cryptography, Probability & Statistics, Public Key Cryptography Standards (PKCS), Arithmetic, Algorithms, Mathematical Modeling, Network Analysis, Encryption, Data Structures, Mathematical Theory & Analysis, Operations Research, Computer Security
4.5
Rating, 4.5 out of 5 stars
3.6K reviews
Beginner · Specialization · 3 - 6 Months
Status: Preview
Shanghai Jiao Tong University
Discrete Mathematics
Skills you'll gain: Graph Theory, Combinatorics, Theoretical Computer Science, Mathematical Theory & Analysis, Network Analysis, Advanced Mathematics, Computer Science, Data Structures, Algorithms, Computational Thinking, Probability
3.3
Rating, 3.3 out of 5 stars
199 reviews
Intermediate · Course · 1 - 3 Months
Status: Preview
Peking University
离散数学概论 Discrete Mathematics Generality
Skills you'll gain: Theoretical Computer Science, Computational Logic, Graph Theory, Logical Reasoning, Deductive Reasoning, Mathematics and Mathematical Modeling, Spatial Analysis, Computational Thinking, Network Analysis, Algebra, Algorithms
4.7
Rating, 4.7 out of 5 stars
280 reviews
Beginner · Course · 3 - 6 Months
Status: New
Status: Preview
University of Colorado Boulder
Introduction to Python for Scientific Computing
Skills you'll gain: Scientific Visualization, NumPy, Data Visualization, Matplotlib, Debugging, Numerical Analysis, Engineering Calculations, Integrated Development Environments, Programming Principles, Computational Thinking, Engineering Analysis, Data Analysis, Computer Programming
Beginner · Course · 1 - 4 Weeks
Status: Preview
Stanford University
Introduction to Mathematical Thinking
Skills you'll gain: Mathematical Theory & Analysis, Mathematics and Mathematical Modeling, Deductive Reasoning, Calculus, Logical Reasoning, Computational Logic, General Mathematics
4.8
Rating, 4.8 out of 5 stars
2.9K reviews
Intermediate · Course · 1 - 3 Months
Status: Preview
Stanford University
Introduction to Logic
Skills you'll gain: Computational Logic, Logical Reasoning, Computational Thinking, Theoretical Computer Science, Computer Science, Problem Solving, Technology Solutions, Relational Databases, Verification And Validation
4.4
Rating, 4.4 out of 5 stars
651 reviews
Intermediate · Course · 1 - 3 Months

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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, Graph Theory, Artificial Neural Networks, Python Programming, Algorithms
4.6
Rating, 4.6 out of 5 stars
15K reviews
Beginner · Specialization · 3 - 6 Months
Status: Free Trial
The Hong Kong University of Science and Technology
Mathematics for Engineers
Skills you'll gain: Linear Algebra, Matlab, Differential Equations, Integral Calculus, Numerical Analysis, Engineering Calculations, Engineering Analysis, Applied Mathematics, Finite Element Methods, Calculus, Algebra, Geometry, Advanced Mathematics, Engineering, General Mathematics, Mathematical Modeling, Mechanical Engineering, Scripting, Vibrations, Simulation and Simulation Software
4.8
Rating, 4.8 out of 5 stars
7.6K reviews
Beginner · Specialization · 3 - 6 Months
Status: Preview
Duke University
Data Science Math Skills
Skills you'll gain: Probability, General Mathematics, Bayesian Statistics, Calculus, Graphing, Descriptive Statistics, Algebra, Derivatives
4.5
Rating, 4.5 out of 5 stars
13K reviews
Beginner · Course · 1 - 3 Months
Status: Free Trial
Johns Hopkins University
Linear Algebra from Elementary to Advanced
Skills you'll gain: Linear Algebra, Applied Mathematics, Algebra, Image Analysis, Applied Machine Learning, Engineering Calculations, Geometry, Advanced Mathematics, Mathematical Modeling, Markov Model, Numerical Analysis, Data Transformation
4.7
Rating, 4.7 out of 5 stars
195 reviews
Beginner · Specialization · 3 - 6 Months
Status: Free Trial
University of California San Diego
Data Structures and Algorithms
Skills you'll gain: Data Structures, Graph Theory, Algorithms, Computational Thinking, Bioinformatics, Network Model, Advanced Mathematics, Computer Programming, Theoretical Computer Science, Program Development, Operations Research, System Design and Implementation, Network Analysis, Network Routing, Programming Principles, Linear Algebra, Text Mining, C (Programming Language), Software Testing, Debugging
4.6
Rating, 4.6 out of 5 stars
17K reviews
Intermediate · 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