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

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Результатов для запроса ''discrete mathematics': 91

IBM Skills Network
Data Science Fundamentals with Python and SQL
Получаемые навыки: Basic Descriptive Statistics, Business Analysis, Computational Logic, Computer Programming, Correlation And Dependence, Data Analysis, Data Management, Data Visualization, Database Administration, Database Application, Databases, Extract, Transform, Load, General Statistics, Machine Learning, Mathematical Theory & Analysis, Mathematics, Plot (Graphics), Probability & Statistics, Probability Distribution, Python Programming, R Programming, Regression, SPSS, SQL, Statistical Analysis, Statistical Programming, Statistical Tests, Statistical Visualization, Theoretical Computer Science
4.5
(рецензий: 47.5k)
Beginner · Specialization · 3-6 Months
DeepLearning.AI
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Получаемые навыки: Probability & Statistics, Python Programming, Mathematics, Probability Distribution, Statistical Machine Learning, Applied Machine Learning, Algorithms, Linearity, Regression, Theoretical Computer Science, Linear Algebra, Statistical Classification, Linear Regression, Computer Programming, Econometrics, Logistic Regression, Feature Engineering, Accounting, General Statistics, Statistical Programming, Calculus, Machine Learning, Cost, Artificial Neural Networks, Machine Learning Algorithms
4.9
(рецензий: 1.8k)
Beginner · Course · 1-4 Weeks
IBM Skills Network
IBM AI Engineering
Получаемые навыки: Algorithms, Apache, Applied Machine Learning, Artificial Neural Networks, Basic Descriptive Statistics, Big Data, Business Analysis, Computer Graphic Techniques, Computer Graphics, Computer Programming, Computer Vision, Correlation And Dependence, Data Analysis, Data Clustering Algorithms, Data Management, Data Structures, Databases, Deep Learning, Dimensionality Reduction, Econometrics, Entrepreneurship, General Statistics, Machine Learning, Machine Learning Algorithms, Mathematics, NoSQL, Probability & Statistics, Probability Distribution, Python Programming, Regression, SQL, Statistical Analysis, Statistical Machine Learning, Statistical Programming, Supply Chain Systems, Supply Chain and Logistics, Tensorflow, Theoretical Computer Science
4.6
(рецензий: 14.7k)
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Columbia University
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4.4
(рецензий: 78)
Intermediate · Specialization · 3-6 Months
Imperial College London
Statistical Analysis with R for Public Health
Получаемые навыки: Analysis, Bayesian Statistics, Business Analysis, Correlation And Dependence, Data Analysis, Econometrics, General Statistics, Machine Learning, Machine Learning Algorithms, Mathematics, Probability & Statistics, Probability Distribution, R Programming, Regression, Statistical Analysis, Statistical Programming, Statistical Tests
4.7
(рецензий: 1.6k)
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Johns Hopkins University
Advanced Statistics for Data Science
Получаемые навыки: Algebra, Artificial Neural Networks, Bayesian Statistics, Biostatistics, Calculus, Communication, Dimensionality Reduction, Econometrics, Experiment, General Statistics, Linear Algebra, Machine Learning, Machine Learning Algorithms, Mathematics, Probability & Statistics, Probability Distribution, Regression, Statistical Machine Learning, Statistical Tests
4.4
(рецензий: 660)
Advanced · Specialization · 3-6 Months
University of Colorado Boulder
Expressway to Data Science: Essential Math
Получаемые навыки: Accounting, Algebra, Algorithms, Big Data, Calculus, Computer Graphic Techniques, Computer Graphics, Computer Programming, Corporate Accouting, Data Analysis, Data Management, Data Mining, Data Model, Data Structures, Design and Product, Differential Equations, Finance, General Statistics, Investment Management, Linear Algebra, Mathematical Theory & Analysis, Mathematics, Probability & Statistics, Probability Distribution, Product Design, Programming Principles, Software Architecture, Software Engineering, Theoretical Computer Science
4.4
(рецензий: 73)
Intermediate · Specialization · 3-6 Months
Бесплатно
University of Pennsylvania
Finance & Quantitative Modeling for Analysts
Получаемые навыки: Accounting, Accounts Payable and Receivable, Analysis, Business Analysis, Corporate Bond, Data Analysis, Data Analysis Software, Design and Product, Entrepreneurship, Finance, Financial Accounting, Financial Analysis, Forecasting, General Accounting, General Statistics, Investment Management, Leadership and Management, Market Research, Marketing, Mathematics, Microsoft Excel, Probability, Probability & Statistics, Probability Distribution, Product Management, Product Marketing, Regression, Research and Design, Sales, Spreadsheet Software, Strategy, Strategy and Operations, Taxes
4.5
(рецензий: 14.5k)
Beginner · Specialization · 3-6 Months
University of Pennsylvania
Business and Financial Modeling
Получаемые навыки: Accounting, Accounts Payable and Receivable, Basic Descriptive Statistics, Business Analysis, Cash Management, Corporate Accouting, Correlation And Dependence, Data Analysis, Data Analysis Software, Data Management, Data Model, Decision Making, Design and Product, Entrepreneurship, Finance, Financial Accounting, Financial Analysis, Flow Network, Forecasting, General Statistics, Investment Management, Leadership and Management, Market Research, Marketing, Mathematics, Microsoft Excel, Performance Management, Probability, Probability & Statistics, Probability Distribution, Problem Solving, Product Management, Product Marketing, Regression, Research and Design, Risk Management, Sales, Simulation, Spreadsheet Software, Statistical Analysis, Statistical Tests, Strategy, Strategy and Operations
4.5
(рецензий: 9.8k)
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DeepLearning.AI
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4.9
(рецензий: 307)
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DeepLearning.AI
Unsupervised Learning, Recommenders, Reinforcement Learning
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4.9
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Результаты поиска, связанного с discrete mathematics

离散数学概论 discrete mathematics generality

10 самых популярных курсов по запросу discrete mathematics

Data Science Fundamentals with Python and SQL: IBM Skills Network
Supervised Machine Learning: Regression and Classification: DeepLearning.AI
IBM AI Engineering: IBM Skills Network
Financial Engineering and Risk Management: Columbia University
Statistical Analysis with R for Public Health: Imperial College London
Advanced Statistics for Data Science: Johns Hopkins University
Expressway to Data Science: Essential Math: University of Colorado Boulder
Calculus: Single Variable Part 2 - Differentiation: University of Pennsylvania
Finance & Quantitative Modeling for Analysts: University of Pennsylvania
Business and Financial Modeling: University of Pennsylvania

Навыки, которые вы можете получить здесь: Probability And Statistics

Программирование На Языке R (19)

Заключение (16)

Линейная Регрессия (12)

Статистический Анализ (12)

Статистический Вывод (11)

Регрессионный Анализ (10)

Биостатистика (9)

Байесовский (7)

Логистическая Регрессия (7)

Распределение Вероятностей (7)

Байесовская Статистика (6)

Медицинская Статистика (6)

Часто задаваемые вопросы на тему 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.‎

Часто задаваемые вопросы предоставляются в ознакомительных целях. Учащимся рекомендуется дополнительно убедиться в том, что интересующие их курсы и другие материалы соответствуют их личным, профессиональным и финансовым потребностям.