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In mathematics and computer science, an algorithm (/ ˈ æ l ɡ ə r ɪ ð əm / ⓘ) is a finite sequence of mathematically rigorous instructions, typically used to solve a class of specific problems or to perform a computation. [1] Algorithms are used as specifications for performing calculations and data processing.
The NIST Dictionary of Algorithms and Data Structures [1] is a reference work maintained by the U.S. National Institute of Standards and Technology. It defines a large number of terms relating to algorithms and data structures. For algorithms and data structures not necessarily mentioned here, see list of algorithms and list of data structures.
Assessment for AP Computer Science Principles is divided into two parts: a Create Performance Task due during the course, as well as an AP exam. [2] AP Computer Science Principles examines a variety of computing topics on a largely conceptual level, and teaches procedural programming. In the Create "Through-Course Assessment", students must ...
Computer science is the study of computation, information, and automation. [1] [2] [3] Computer science spans theoretical disciplines (such as algorithms, theory of computation, and information theory) to applied disciplines (including the design and implementation of hardware and software). [4] [5] [6]
Software engineering – The principles and practice of designing, developing, and testing programs, as well as proper engineering practices. Algorithm design – Using ideas from algorithm theory to creatively design solutions to real tasks. Computer programming – The practice of using a programming language to implement algorithms.
Modern cryptography is heavily based on mathematical theory and computer science practice; cryptographic algorithms are designed around computational hardness assumptions, making such algorithms hard to break in practice by any adversary. It is theoretically possible to break such a system, but it is infeasible to do so by any known practical ...
It teaches fundamental principles of computer programming, including recursion, abstraction, modularity, and programming language design and implementation. MIT Press published the first edition in 1984, and the second edition in 1996. It was used as the textbook for MIT's introductory course in computer science from 1984 to 2007.
In supervised learning, an algorithm is given samples that are labeled in some useful way. For example, the samples might be descriptions of mushrooms, and the labels could be whether or not the mushrooms are edible. The algorithm takes these previously labeled samples and uses them to induce a classifier.