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.

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''discrete mathematics'的 131 个结果

University of California San Diego
Introduction to Discrete Mathematics for Computer Science
您将获得的技能： Mathematics, Graph Theory, Computer Science, Computer Programming, Python Programming, Statistical Programming, Data Science, Algebra, Theoretical Computer Science, Probability & Statistics, Algorithms, Calculus, Combinatorics, Data Analysis, Statistical Analysis, General Statistics, Mathematical Theory & Analysis, Programming Principles, Bayesian Statistics, Computational Thinking, Geometry, Applied Mathematics, Correlation And Dependence, Estimation, Probability Distribution, Computational Logic, Business Analysis, Communication, Computer Architecture, Critical Thinking, Cryptography, Data Visualization, Entrepreneurship, Leadership and Management, Machine Learning, Markov Model, Microarchitecture, Problem Solving, Research and Design, Scientific Visualization, Security Engineering, Statistical Visualization, Strategy and Operations
4.5
（3.3k 条评论）
Beginner · Specialization · 3-6 Months
University of London
Bachelor of Science in Computer Science
您将获得的技能： Computer Programming, Theoretical Computer Science, Web Development, Mathematics, Algorithms, Data Management, Databases, C Programming Language Family, Javascript, Software Engineering, C++ Programming, Programming Principles, Statistical Programming, Data Structures, Mathematical Theory & Analysis, Operating Systems, SQL, Computer Graphics, Machine Learning, Probability & Statistics, Computational Logic, Computer Architecture, Software Testing, Computer Networking, Human Computer Interaction, Security Engineering, Data Analysis, Python Programming, Agile Software Development, Network Security, Regression, Mobile Development, Software Architecture, Software Security, System Security, Algebra, Full-Stack Web Development, General Statistics, HTML and CSS, Interactive Design, Linear Algebra, Network Architecture, Network Model, Other Programming Languages, Probability Distribution, User Experience, Web Design, Design and Product, Product Design, Data Visualization, Artificial Neural Networks, Back-End Web Development, Business Psychology, Calculus, Cloud Computing, Cloud Storage, Combinatorics, Computational Thinking, Computer Programming Tools, Database Design, Front-End Web Development, Graph Theory, Leadership and Management, Microarchitecture, Natural Language Processing, Professional Development, Research and Design, System Programming, User Experience Design, Internet Of Things, Journalism, Software Engineering Tools
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Degree · 1-4 Years
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Imperial College London
Mathematics for Machine Learning
您将获得的技能： Mathematics, Algebra, Linear Algebra, Machine Learning, Python Programming, Probability & Statistics, General Statistics, Calculus, Computer Programming, Applied Mathematics, Mathematical Theory & Analysis, Statistical Programming, Algorithms, Dimensionality Reduction, Regression, Theoretical Computer Science, Basic Descriptive Statistics, Data Analysis, Probability Distribution, Artificial Neural Networks, Computer Graphic Techniques, Computer Graphics, Computer Networking, Deep Learning, Differential Equations, Experiment, Machine Learning Algorithms, Network Model
4.6
（13.4k 条评论）
Beginner · Specialization · 3-6 Months
免费
Stanford University
Introduction to Statistics
您将获得的技能： Data Science, General Statistics, Probability & Statistics, Statistical Tests, Estimation, Basic Descriptive Statistics, Correlation And Dependence, Probability Distribution, Regression, Bayesian Statistics, Data Analysis, Data Visualization, Econometrics, Experiment, Machine Learning, Markov Model, Plot (Graphics), Statistical Analysis, Statistical Visualization
4.5
（1.9k 条评论）
Beginner · Course · 1-3 Months
University of Colorado Boulder
Expressway to Data Science: Essential Math
您将获得的技能： Mathematics, Algebra, Calculus, Linear Algebra, Mathematical Theory & Analysis, Differential Equations, Theoretical Computer Science, Probability & Statistics, Algorithms, Entrepreneurship, Graph Theory, Leadership and Management, Probability Distribution, Problem Solving, Research and Design, Computer Graphic Techniques, Computer Graphics, General Statistics, Accounting, Big Data, Computer Programming, Corporate Accouting, Data Analysis, Data Management, Data Mining, Data Model, Data Structures, Design and Product, Finance, Investment Management, Product Design, Programming Principles, Software Architecture, Software Engineering
4.5
（197 条评论）
Intermediate · Specialization · 3-6 Months
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免费
免费
University of California San Diego
Mathematical Thinking in Computer Science
您将获得的技能： Mathematics, Algebra, Geometry, Algorithms, Applied Mathematics, Computational Thinking, Theoretical Computer Science, Computational Logic, Business Analysis, Computer Programming, Critical Thinking, Leadership and Management, Mathematical Theory & Analysis, Problem Solving, Programming Principles, Python Programming, Research and Design, Statistical Programming, Strategy and Operations
4.4
（2.1k 条评论）
Beginner · Course · 1-3 Months

与 discrete mathematics 相关的搜索

introduction to discrete mathematics for computer science

离散数学概论 discrete mathematics generality

总之，这是我们最受欢迎的 discrete mathematics 门课程中的 10 门

Introduction to Discrete Mathematics for Computer Science: University of California San Diego
Bachelor of Science in Computer Science: University of London
Discrete Mathematics: Shanghai Jiao Tong University
离散数学概论 Discrete Mathematics Generality: Peking University
Mathematics for Machine Learning: Imperial College London
Introduction to Statistics: Stanford University
Data Science Foundations: Statistical Inference: University of Colorado Boulder
Expressway to Data Science: Essential Math: University of Colorado Boulder
Basic Modeling for Discrete Optimization: The University of Melbourne
Data Science Math Skills: Duke University

您可以在 Probability And Statistics 中学到的技能

关于 Discrete Mathematics 的常见问题

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.‎