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Discrete Mathematics Courses Online

Master discrete mathematics for computer science and engineering. Learn about logic, set theory, combinatorics, graph theory, and algorithms.

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Explore the Discrete Mathematics Course Catalog

  • Status: Free Trial
    Free Trial
    U

    University of California San Diego

    Introduction to Discrete Mathematics for Computer Science

    Skills you'll gain: Graph Theory, Logical Reasoning, Cryptographic Protocols, Combinatorics, Computational Logic, Deductive Reasoning, Cryptography, Probability, Key Management, Computational Thinking, Encryption, Probability Distribution, Network Analysis, Public Key Cryptography Standards (PKCS), Theoretical Computer Science, Bayesian Statistics, Python Programming, Data Structures, Algorithms, Arithmetic

    4.5
    Rating, 4.5 out of 5 stars
    ·
    3.7K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Preview
    Preview
    S

    Shanghai Jiao Tong University

    Discrete Mathematics

    Skills you'll gain: Combinatorics, Graph Theory, Theoretical Computer Science, Mathematical Theory & Analysis, Advanced Mathematics, Network Analysis, Computational Thinking, Algorithms, Data Structures, Computer Science

    3.3
    Rating, 3.3 out of 5 stars
    ·
    200 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    B

    Birla Institute of Technology & Science, Pilani

    Discrete Mathematics for Computer Science and Engineering

    Skills you'll gain: Theoretical Computer Science, Programming Principles, Cryptography, Algorithms, Applied Mathematics, Probability & Statistics, Data Management

    Beginner · Course · 1 - 3 Months

  • Status: Preview
    Preview
    P

    Peking University

    离散数学概论 Discrete Mathematics Generality

    Skills you'll gain: Computational Logic, Theoretical Computer Science, Graph Theory, Logical Reasoning, Computational Thinking, Geospatial Information and Technology, Information Technology, Algebra, Computer Science, Algorithms

    4.7
    Rating, 4.7 out of 5 stars
    ·
    281 reviews

    Beginner · Course · 3 - 6 Months

  • Status: Preview
    Preview
    S

    Stanford University

    Introduction to Mathematical Thinking

    Skills you'll gain: Mathematical Theory & Analysis, Mathematics and Mathematical Modeling, Calculus, Deductive Reasoning, Logical Reasoning

    4.8
    Rating, 4.8 out of 5 stars
    ·
    3K reviews

    Intermediate · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    U

    University of Pittsburgh

    Mathematical Foundations for Data Science and Analytics

    Skills you'll gain: Statistical Analysis, NumPy, Probability Distribution, Matplotlib, Statistics, Pandas (Python Package), Data Science, Probability & Statistics, Probability, Statistical Modeling, Predictive Modeling, Data Analysis, Linear Algebra, Predictive Analytics, Statistical Methods, Mathematics and Mathematical Modeling, Applied Mathematics, Python Programming, Machine Learning, Logical Reasoning

    Build toward a degree

    Beginner · Specialization · 1 - 3 Months

What brings you to Coursera today?

  • Status: New
    New
    Status: Free Trial
    Free Trial
    B

    Birla Institute of Technology & Science, Pilani

    Mathematics for Engineering

    Skills you'll gain: Integral Calculus, Engineering Calculations, Data Analysis, Probability & Statistics, Engineering Analysis, Computational Logic, Statistical Analysis, Linear Algebra, Logical Reasoning, Deductive Reasoning, Mathematical Modeling, Trigonometry, Analytics, Bayesian Statistics, Statistical Modeling, Artificial Intelligence and Machine Learning (AI/ML), Statistical Inference, Theoretical Computer Science, Programming Principles, Descriptive Analytics

    4.6
    Rating, 4.6 out of 5 stars
    ·
    156 reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    Imperial College London

    Mathematics for Machine Learning

    Skills you'll gain: Linear Algebra, Dimensionality Reduction, NumPy, Regression Analysis, Calculus, Applied Mathematics, Machine Learning Algorithms, Jupyter, Data Science, Advanced Mathematics, Statistics, Geometry, Statistical Analysis, Artificial Neural Networks, Algorithms, Data Manipulation, Python Programming, Machine Learning, Derivatives

    4.6
    Rating, 4.6 out of 5 stars
    ·
    15K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    T

    The Hong Kong University of Science and Technology

    Mathematics for Engineers

    Skills you'll gain: Differential Equations, Linear Algebra, Matlab, Engineering Calculations, Engineering Analysis, Numerical Analysis, Finite Element Methods, Integral Calculus, Mathematical Software, Mechanical Engineering, Calculus, Algebra, Applied Mathematics, Mathematical Modeling, Engineering, Simulation and Simulation Software, Advanced Mathematics, Geometry, Computational Thinking, Estimation

    4.8
    Rating, 4.8 out of 5 stars
    ·
    7.6K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    D

    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, Linear Algebra, Statistical Inference, A/B Testing, Statistical Analysis, Applied Mathematics, NumPy, Probability, Calculus, Dimensionality Reduction, Numerical Analysis, Mathematical Modeling, Machine Learning, Machine Learning Methods, Data Transformation

    4.6
    Rating, 4.6 out of 5 stars
    ·
    2.9K reviews

    Intermediate · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Linear Algebra from Elementary to Advanced

    Skills you'll gain: Linear Algebra, Algebra, Applied Mathematics, Artificial Intelligence and Machine Learning (AI/ML), Mathematical Modeling, Advanced Mathematics, Engineering Analysis, Mathematical Theory & Analysis, Numerical Analysis, Geometry, Graph Theory, Applied Machine Learning, Markov Model, Probability

    4.7
    Rating, 4.7 out of 5 stars
    ·
    200 reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    U

    University of London

    Mathematics for Computer Science

    Skills you'll gain: Arithmetic, Computer Graphics, Computational Thinking, General Mathematics, Systems Of Measurement, Algebra, Cryptography

    4.2
    Rating, 4.2 out of 5 stars
    ·
    253 reviews

    Beginner · Course · 1 - 4 Weeks

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1234…62

In summary, here are 10 of our most popular discrete mathematics courses

  • Introduction to Discrete Mathematics for Computer Science: University of California San Diego
  • Discrete Mathematics: Shanghai Jiao Tong University
  • Discrete Mathematics for Computer Science and Engineering: Birla Institute of Technology & Science, Pilani
  • 离散数学概论 Discrete Mathematics Generality: Peking University
  • Introduction to Mathematical Thinking: Stanford University
  • Mathematical Foundations for Data Science and Analytics: University of Pittsburgh
  • Mathematics for Engineering: Birla Institute of Technology & Science, Pilani
  • Mathematics for Machine Learning: Imperial College London
  • Mathematics for Engineers: The Hong Kong University of Science and Technology
  • Mathematics for Machine Learning and Data Science: DeepLearning.AI

Skills you can learn in Probability And Statistics

R Programming (19)
Inference (16)
Linear Regression (12)
Statistical Analysis (12)
Statistical Inference (11)
Regression Analysis (10)
Biostatistics (9)
Bayesian (7)
Logistic Regression (7)
Probability Distribution (7)
Bayesian Statistics (6)
Medical Statistics (6)

Frequently Asked Questions about 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.‎

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. ‎

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.‎

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.‎

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.‎

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.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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