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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University of Pennsylvania
Master of Computer and Information Technology
Kompetenzen, die Sie erwerben: Theoretical Computer Science, Computer Programming, Databases, Data Management, Mathematics, Data Structures, Java Programming, Mobile Development, Statistical Programming, Algorithms, Operating Systems, Python Programming, Probability & Statistics, Graph Theory, Software Engineering, Mathematical Theory & Analysis, General Statistics, SQL, Design and Product, Product Design, Software Architecture, Combinatorics, System Programming, Probability Distribution, Software Testing, Agile Software Development, Computer Graphic Techniques, Computer Graphics, Software Framework, Operations Research, Research and Design, Strategy and Operations, Data Visualization, Database Design, Linear Algebra, Programming Principles, Statistical Machine Learning, Computer Networking, Network Architecture, Computer Architecture, Bayesian Statistics, Correlation And Dependence, Data Analysis, Database Theory, Dimensionality Reduction, Estimation, Machine Learning Algorithms, Regression, Software Engineering Tools, Advertising, Algebra, Application Development, BlockChain, Communication, Cryptography, Finance, Human Computer Interaction, Javascript, Journalism, Marketing, Security Engineering, Web Development
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DeepLearning.AI
Mathematics for Machine Learning and Data Science
Kompetenzen, die Sie erwerben: Linear Algebra, Mathematics, Mathematical Theory & Analysis, Algebra, Algorithms, Artificial Neural Networks, Computer Programming, Deep Learning, Machine Learning, Python Programming, Statistical Programming, Theoretical Computer Science, Calculus, Statistical Analysis
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Beginner · Specialization · 1-3 Months
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The University of Melbourne
Discrete Optimization
Kompetenzen, die Sie erwerben: Computer Science, Mathematics, Applied Mathematics, Computer Programming, Geometry, Linear Algebra, Python Programming, Algorithms, Entrepreneurship, Graph Theory, Market Research, Operations Research, Programming Principles, Research and Design, Software Engineering, Software Testing, Statistical Programming, Strategy and Operations, Theoretical Computer Science
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Imperial College London
Mathematics for Machine Learning: PCA
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DeepLearning.AI, Stanford University
Machine Learning
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DeepLearning.AI
Deep Learning
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DeepLearning.AI
Supervised Machine Learning: Regression and Classification
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Suchanfragen mit Bezug zu discrete mathematics

introduction to discrete mathematics for computer science

离散数学概论 discrete mathematics generality

Zusammenfassend sind hier 10 unserer beliebtesten discrete mathematics Kurse

Master of Computer and Information Technology: University of Pennsylvania
Delivery Problem: University of California San Diego
Asymmetric Cryptography and Key Management: University of Colorado System
离散数学: Shanghai Jiao Tong University
Fibonacci Numbers and the Golden Ratio: The Hong Kong University of Science and Technology
Mathematics for Machine Learning and Data Science: DeepLearning.AI
Discrete Optimization: The University of Melbourne
Mathematics for Machine Learning: PCA: Imperial College London
Solving Algorithms for Discrete Optimization: The University of Melbourne
Machine Learning: DeepLearning.AI

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Häufig gestellte Fragen zum Thema 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.‎

Diese häufig gestellten Fragen dienen nur zu Informationszwecken. Den Lernenden wird empfohlen, eingehender zu recherchieren, ob Kurse und andere angestrebte Qualifikationen wirklich ihren persönlichen, beruflichen und finanziellen Vorstellungen entsprechen.