Logic is the study of reasoning, which is a method of thinking that helps people decide what’s true or false. It often involves writing out statements to reach a conclusion about whether something is true or it exists in a certain way. For example, if A = B and B = C, does A = C? While this transitive law is an important element of logic, and one many of us might think of when we imagine the concept itself, there’s plenty of other interesting things to learn about this area of study. Logic is important in the study of philosophy and social sciences. It’s also vital in the fields of mathematics, including statistics and data analysis, and in computer programming, which utilizes logic to run the algorithms that power programs and interpret and compile data.

Why is logic important to learn?

Studying logic helps you form better arguments when writing papers or engaging in a debate with someone, and it can improve your critical thinking skills as you consume media and advertising. It’s also an essential concept in computing and mathematics, where knowing how to formulate logical proofs is a foundational aspect of programming and working with different theories. Logic may seem like an esoteric concept relegated to robed philosophers of yore, but it’s possibly more relevant than ever in today’s world.

What are typical careers that use logic?

Careers that allow you to put your knowledge of logic to work include jobs as a banker or finance professional, doctor, detective and lawyer, but work as a computer programmer also often utilizes logic — both from you and in the programs you write. Logical thinking isn’t limited to one career field — there’s a whole world of opportunity out there that you can access as you learn more about logic concepts, whether they involve critical thinking and mathematical thinking and other reasoning skills. You’ll apply it while solving problems, while configuring data structures and even while assessing code other programmers have written. Knowledge of logic helps you learn to think differently, which you can use to your benefit in any career you dream of.

How can online courses help me learn logic?

Signing up for online courses on Coursera can open you up to a new world of innovative learning when you’re ready to develop those new-to-you skills in an environment that makes discoveries more accessible than ever before. Logical thinking is essential in everyday life, and it’s also one of the fundamental skills you’ll call on if you’re pursuing a career in computer science or programming. To started with the basics, take a course that teaches you how to construct inductive arguments and recognize fallacies as you’re introduced to basic concepts in logic and critical thinking. When you're ready for more, consider earning a specialization in discrete mathematics as you learn the role of logic in mathematical thinking. What you study and when are up to you, and taking online classes removes obstacles to pursuing topics you find fascinating.

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1516 Ergebnisse für „logic“

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Universitat Autònoma de Barcelona
Digital Systems: From Logic Gates to Processors
Kompetenzen, die Sie erwerben: Computer Architecture, Computational Logic, Theoretical Computer Science, Algebra, Business Analysis, Critical Thinking, Hardware Design, Mathematics, Microarchitecture, Research and Design, Strategy and Operations, Algorithms, Computer Programming, Data Analysis, Programming Principles
4.4
(704 Bewertungen)
Intermediate · Course · 1-3 Months
University of Illinois at Urbana-Champaign
VLSI CAD Part I: Logic
Kompetenzen, die Sie erwerben: Theoretical Computer Science, Computational Logic, Algorithms, Computer Architecture, Computer Programming, Microarchitecture, Algebra, C Programming Language Family, Computational Thinking, Computer Science, Deep Learning, Machine Learning, Mathematics
4.7
(515 Bewertungen)
Intermediate · Course · 1-3 Months
University of Colorado Boulder
Methods for Solving Problems
Kompetenzen, die Sie erwerben: Research and Design, Business Analysis, Critical Thinking, Strategy and Operations, Entrepreneurship, Leadership and Management, Problem Solving, Leadership Development, Computational Logic, Decision Making, General Statistics, Probability & Statistics, Probability Distribution, Theoretical Computer Science
4.4
(160 Bewertungen)
Beginner · Course · 1-4 Weeks
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Google
Google Data Analytics
Kompetenzen, die Sie erwerben: Data Analysis, Data Science, Statistical Programming, Business Analysis, SQL, Spreadsheet Software, Business, Data Visualization, Data Management, R Programming, Exploratory Data Analysis, Statistical Visualization, Communication, Statistical Analysis, Data Analysis Software, Business Communication, Data Structures, Data Visualization Software, Tableau Software, Big Data, Cloud Computing, Collaboration, Conflict Management, Critical Thinking, Customer Analysis, General Statistics, Leadership and Management, Plot (Graphics), Probability & Statistics, Small Data, Algorithms, Application Development, Budget Management, Computational Logic, Computer Architecture, Computer Networking, Computer Programming, Computer Programming Tools, Cryptography, Data Mining, Data Model, Database Administration, Database Design, Databases, Decision Making, Design and Product, Distributed Computing Architecture, Entrepreneurship, Extract, Transform, Load, Feature Engineering, Finance, Full-Stack Web Development, Interactive Data Visualization, Machine Learning, Mathematical Theory & Analysis, Mathematics, Network Security, Other Programming Languages, Problem Solving, Product Design, Programming Principles, Project Management, Research and Design, Security Engineering, Security Strategy, Software Engineering, Software Security, Storytelling, Theoretical Computer Science, Visual Design, Visualization (Computer Graphics), Web Development
4.8
(108.1k Bewertungen)
Beginner · Professional Certificate · 3-6 Months
IBM Skills Network
IBM Data Science
Kompetenzen, die Sie erwerben: Python Programming, Data Science, Data Analysis, Data Structures, Statistical Programming, Machine Learning, Data Mining, Regression, Machine Learning Algorithms, Data Visualization, General Statistics, Basic Descriptive Statistics, SQL, Applied Machine Learning, Statistical Analysis, Computer Programming Tools, Data Analysis Software, Machine Learning Software, Software Visualization, Databases, Programming Principles, Exploratory Data Analysis, Computer Programming, Statistical Visualization, Algebra, Data Management, Database Theory, Data Visualization Software, R Programming, Statistical Machine Learning, Statistical Tests, Deep Learning, Probability & Statistics, Extract, Transform, Load, Plot (Graphics), Devops Tools, SPSS, Estimation, Interactive Data Visualization, Algorithms, Database Application, Geovisualization, Reinforcement Learning, Theoretical Computer Science, Big Data, Business Analysis, Computational Logic, Correlation And Dependence, Database Administration, Econometrics, Entrepreneurship, Marketing, Mathematical Theory & Analysis, Mathematics, Spreadsheet Software, Storytelling, Supply Chain Systems, Supply Chain and Logistics, Writing
4.6
(108.5k Bewertungen)
Beginner · Professional Certificate · 3-6 Months
IBM Skills Network
IBM Data Analyst
Kompetenzen, die Sie erwerben: Data Analysis, Python Programming, Data Visualization, Exploratory Data Analysis, Basic Descriptive Statistics, Data Structures, Statistical Programming, Data Science, Statistical Visualization, Plot (Graphics), Data Management, General Statistics, SQL, Databases, Business Analysis, Microsoft Excel, Spreadsheet Software, Data Mining, Statistical Analysis, Programming Principles, Probability & Statistics, Regression, Machine Learning, Algebra, Computer Programming, Data Analysis Software, Database Theory, Probability Distribution, Applied Machine Learning, Statistical Tests, Big Data, Correlation And Dependence, Data Visualization Software, Estimation, NoSQL, Geovisualization, ArcGIS, Cloud Computing, Data Warehousing, Database Application, Extract, Transform, Load, HTML and CSS, Knitr, Mathematics, Minitab, PostgreSQL, R Programming, SAS (Software), SPSS, Apache, Computational Logic, Computer Programming Tools, Database Administration, Econometrics, Interactive Data Visualization, Leadership and Management, Mathematical Theory & Analysis, Operating Systems, Professional Development, Statistical Machine Learning, System Programming, Theoretical Computer Science
4.6
(62.6k Bewertungen)
Beginner · Professional Certificate · 3-6 Months
DeepLearning.AI, Stanford University
Machine Learning
Kompetenzen, die Sie erwerben: Machine Learning, Probability & Statistics, Machine Learning Algorithms, General Statistics, Theoretical Computer Science, Applied Machine Learning, Algorithms, Artificial Neural Networks, Regression, Econometrics, Computer Programming, Deep Learning, Python Programming, Statistical Programming, Mathematics, Tensorflow, Data Management, Data Structures, Statistical Machine Learning, Reinforcement Learning, Probability Distribution, Mathematical Theory & Analysis, Data Analysis, Data Mining, Linear Algebra, Computer Vision, Calculus, Feature Engineering, Bayesian Statistics, Operations Research, Research and Design, Strategy and Operations, Computational Logic, Accounting, Communication
4.9
(9.6k Bewertungen)
Beginner · Specialization · 1-3 Months
IBM Skills Network
Data Science Fundamentals with Python and SQL
Kompetenzen, die Sie erwerben: Data Structures, Python Programming, Data Analysis, SQL, Statistical Programming, Computer Programming Tools, Data Analysis Software, General Statistics, Machine Learning Software, Probability & Statistics, Software Visualization, Databases, Programming Principles, Algebra, Database Theory, Business Analysis, Data Visualization Software, R Programming, Statistical Analysis, Data Management, Data Science, Basic Descriptive Statistics, Probability Distribution, Statistical Tests, Devops Tools, Machine Learning Algorithms, SPSS, Correlation And Dependence, Data Visualization, Exploratory Data Analysis, Plot (Graphics), Regression, Statistical Visualization, Computer Programming, Database Application, Extract, Transform, Load, Computational Logic, Database Administration, Machine Learning, Mathematical Theory & Analysis, Mathematics, Theoretical Computer Science
4.5
(53.8k Bewertungen)
Beginner · Specialization · 3-6 Months

Suchanfragen mit Bezug zu logic

logic for economists

logic pro

introduction to logic

introduction to logic and critical thinking

pensamento crítico, lógica e argumentação

digital systems: from logic gates to processors

vlsi cad part i: logic

sistemas digitales: de las puertas lógicas al procesador

Zusammenfassend sind hier 10 unserer beliebtesten logic Kurse

Digital Systems: From Logic Gates to Processors: Universitat Autònoma de Barcelona
VLSI CAD Part I: Logic: University of Illinois at Urbana-Champaign
Methods for Solving Problems: University of Colorado Boulder
Reasoning Across the Disciplines: The University of North Carolina at Chapel Hill
Sistemas Digitales: De las puertas lógicas al procesador: Universitat Autònoma de Barcelona
Pensamento Crítico, Lógica e Argumentação: Universidade Estadual de Campinas
Installation et gestion des paquets logiciels sous Linux: Coursera Project Network
Google Data Analytics: Google
IBM Data Science: IBM Skills Network
IBM Data Analyst: IBM Skills Network

Häufig gestellte Fragen zum Thema Logik

Logic is the study of reasoning, which is a method of thinking that helps people decide what’s true or false. It often involves writing out statements to reach a conclusion about whether something is true or it exists in a certain way. For example, if A = B and B = C, does A = C? While this transitive law is an important element of logic, and one many of us might think of when we imagine the concept itself, there’s plenty of other interesting things to learn about this area of study. Logic is important in the study of philosophy and social sciences. It’s also vital in the fields of mathematics, including statistics and data analysis, and in computer programming, which utilizes logic to run the algorithms that power programs and interpret and compile data.‎
Studying logic helps you form better arguments when writing papers or engaging in a debate with someone, and it can improve your critical thinking skills as you consume media and advertising. It’s also an essential concept in computing and mathematics, where knowing how to formulate logical proofs is a foundational aspect of programming and working with different theories. Logic may seem like an esoteric concept relegated to robed philosophers of yore, but it’s possibly more relevant than ever in today’s world.‎
Careers that allow you to put your knowledge of logic to work include jobs as a banker or finance professional, doctor, detective and lawyer, but work as a computer programmer also often utilizes logic — both from you and in the programs you write. Logical thinking isn’t limited to one career field — there’s a whole world of opportunity out there that you can access as you learn more about logic concepts, whether they involve critical thinking and mathematical thinking and other reasoning skills. You’ll apply it while solving problems, while configuring data structures and even while assessing code other programmers have written. Knowledge of logic helps you learn to think differently, which you can use to your benefit in any career you dream of.‎
Signing up for online courses on Coursera can open you up to a new world of innovative learning when you’re ready to develop those new-to-you skills in an environment that makes discoveries more accessible than ever before. Logical thinking is essential in everyday life, and it’s also one of the fundamental skills you’ll call on if you’re pursuing a career in computer science or programming. To started with the basics, take a course that teaches you how to construct inductive arguments and recognize fallacies as you’re introduced to basic concepts in logic and critical thinking. When you're ready for more, consider earning a specialization in discrete mathematics as you learn the role of logic in mathematical thinking. What you study and when are up to you, and taking online classes removes obstacles to pursuing topics you find fascinating.‎

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.