Computer Science is the study of algorithms, including 1 )Their formal and mathematical properties 2 )Their hardware realizations 3 )Their linguistic realizations 4 )Their Applications
Generally, computer science is all about using object-oriented programs to problem solve and create algorithms. By doing so, you can make program the computer to do simple tasks to extremely hard tasks. For example, you can create a program that lists all the factors of a number or a program in which you play a number guessing game with the computer! It gets more complex as you get more skilled with computer science. Eventually, you can learn how to add graphics into it! I
Computer science and computer programming are closely related fields, but they represent different aspects of the broader realm of computing. Here's a breakdown of their relationship: Computer Science: Definition: Computer science is the study of computers and computational systems. It encompasses a wide range of topics, including algorithms, data structures, artificial intelligence, machine learning, computer architecture, software engineering, and more. Focus: Computer science focuses on understanding the principles and theories that underlie the design and functionality of computers. It explores the broader concepts and methodologies involved in solving computational problems. Computer Programming: Definition: Computer programming, often referred to simply as programming or coding, is the process of designing and building executable computer programs. It involves writing code in programming languages to instruct computers to perform specific tasks or solve particular problems. Focus: Computer programming is a practical application of computer science concepts. Programmers use their knowledge of algorithms, data structures, and programming languages to create software applications, scripts, or systems. Relationship: Interdependence: Computer programming is a practical skill within the broader field of computer science. While computer science provides the theoretical foundation and conceptual framework, computer programming is the hands-on implementation of these concepts to create software solutions. Implementation of Concepts: Programmers apply computer science principles when developing software. They use algorithms and data structures to efficiently solve problems, and they leverage their understanding of software engineering to design and build robust and scalable applications. Dynamic Interaction: The relationship between computer science and programming is dynamic. Advances in computer science research often lead to the development of new programming paradigms, languages, and tools, while practical programming experiences contribute to the refinement and validation of computer science theories. In summary, computer science provides the theoretical knowledge and overarching principles, while computer programming is the practical application of that knowledge to create software. They are intertwined, with advancements in one field often influencing the other, making them essential components of the broader field of computing.
Eigenvectors and eigenvalues are important for understanding the properties of expander graphs, which I understand to have several applications in computer science (such as derandomizing random algorithms). They also give rise to a graph partitioning algorithm. Perhaps the most famous application, however, is to Google's PageRank algorithm.
Computer Science deals with engineering aspects of computer hardware and software. To be more clear it will deal about microprocessors, compilers, datastructures, algorithms and fundamental blocks of computer science. Computer scientists deal with inventing faster processors or highly optimized algorithms IT or Information Technology is the application of hardware and software for a business purpose. IT professionals deals with all kinds of business like entertainment, banking, retail or any such and try to provide solutions to business problems using software installed on appropriate hardware. As many a times software solutions may not be available off the shelf so they may write custom programs to meet the business needs
S. Lakshmivarahan has written: 'Analysis and Design of Parallel Algorithms' -- subject(s): Parallel algorithms, Parallel programming (Computer science), Programming, Supercomputers 'Parallel computing using the prefix problem' -- subject(s): Computer algorithms, Parallel programming (Computer science)
Zbigniew Michalewicz has written: 'How to solve it' -- subject(s): Heuristic, Mathematical recreations, Problem solving 'Genetic algorithms + data structures = evolution programs' -- subject(s): Computer algorithms, Computer programs, Data structures (Computer science), Evolutionary programming (Computer science), Genetic algorithms
Elisabeth C. Salander has written: 'Computer search algorithms' -- subject(s): Computer algorithms, Querying (Computer science), Database searching
Gregory L. Heileman has written: 'Data structures, algorithms, and object-oriented programming' -- subject(s): Computer algorithms, Data structures (Computer science), Object-oriented programming (Computer science)
Algorithms are critical to the field of computer science. They embody the logic used to solve a problem. Written in words, they are (computer) language independent, and they allow peer/team review, so that a good design can result.
what is the role of computer in mathematics what is the role of computer in mathematics
Thomas A. Standish has written: 'Data structures, algorithms, and software principles' -- subject(s): Computer algorithms, Data structures (Computer science), Software engineering 'Data structure techniques' -- subject(s): Data structures (Computer science)
Tolga Acar has written: 'High-speed algorithms & architectures for number-theoretic cryptosystems' -- subject(s): Computer algorithms, Data encryption (Computer science), Cryptography
Rolf Drechsler has written: 'Evolutionary algorithms for VLSI CAD' -- subject(s): Evolutionary programming (Computer science), Algorithms, Integrated circuits, Very large scale integration, Genetic programming (Computer science), Computer-aided design 'Formal Verification of Circuits'
Sanjiv Kapoor has written: 'Topics in the design and analysis of combinatorial algorithms' -- subject(s): Combinatorial analysis, Computer algorithms, Data processing, Data structures (Computer science)
Prakash V. Ramanan has written: 'Topics in combinatorial algorithms' -- subject(s): Combinatorial analysis, Computer algorithms, Data processing, Data structures (Computer science)
Robert E. Tarjan has written: 'Data structures and network algorithms' -- subject(s): Computer algorithms, Data structures (Computer science), Trees (Graph theory)