# A report onComputer science and Algorithm

In mathematics and computer science, an algorithm is a finite sequence of rigorous instructions, typically used to solve a class of specific problems or to perform a computation.

- Algorithm

Computer science spans theoretical disciplines (such as algorithms, theory of computation, information theory and automation) to practical disciplines (including the design and implementation of hardware and software).

- Computer science

## Mathematics

Area of knowledge that includes such topics as numbers , formulas and related structures (algebra), shapes and the spaces in which they are contained (geometry), and quantities and their changes (calculus and analysis).

Area of knowledge that includes such topics as numbers , formulas and related structures (algebra), shapes and the spaces in which they are contained (geometry), and quantities and their changes (calculus and analysis).

Mathematics is essential in many fields, including natural sciences, engineering, medicine, finance, computer science and social sciences.

Algorithms - especially their implementation and computational complexity - play a major role in discrete mathematics.

## Cryptography

Practice and study of techniques for secure communication in the presence of adversarial behavior.

Practice and study of techniques for secure communication in the presence of adversarial behavior.

Modern cryptography exists at the intersection of the disciplines of mathematics, computer science, electrical engineering, communication science, and physics.

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 actual practice by any adversary.

## Data structure

In computer science, a data structure is a data organization, management, and storage format that is usually chosen for efficient access to data.

Usually, efficient data structures are key to designing efficient algorithms.

## Programming language

Any set of rules that converts strings, or graphical program elements in the case of visual programming languages, to various kinds of machine code output.

Any set of rules that converts strings, or graphical program elements in the case of visual programming languages, to various kinds of machine code output.

Programming languages are one kind of computer language, and are used in computer programming to implement algorithms.

Programming language theory is a subfield of computer science that deals with the design, implementation, analysis, characterization, and classification of programming languages.

## Computability theory

Computability theory, also known as recursion theory, is a branch of mathematical logic, computer science, and the theory of computation that originated in the 1930s with the study of computable functions and Turing degrees.

Nowadays these are often considered as a single hypothesis, the Church–Turing thesis, which states that any function that is computable by an algorithm is a computable function.

## Computation

Computation is any type of arithmetic or non-arithmetic calculation that follows a well-defined model (e.g., an algorithm).

An especially well-known discipline of the study of computation is computer science.

## Computational geometry

Computational geometry is a branch of computer science devoted to the study of algorithms which can be stated in terms of geometry.

Some purely geometrical problems arise out of the study of computational geometric algorithms, and such problems are also considered to be part of computational geometry.

## Artificial intelligence

Intelligence demonstrated by machines, as opposed to the natural intelligence displayed by animals including humans.

Intelligence demonstrated by machines, as opposed to the natural intelligence displayed by animals including humans.

AI also draws upon computer science, psychology, linguistics, philosophy, and many other fields.

Cukier, Kenneth, "Ready for Robots? How to Think about the Future of AI", Foreign Affairs, vol. 98, no. 4 (July/August 2019), pp. 192–98. George Dyson, historian of computing, writes (in what might be called "Dyson's Law") that "Any system simple enough to be understandable will not be complicated enough to behave intelligently, while any system complicated enough to behave intelligently will be too complicated to understand." (p. 197.) Computer scientist Alex Pentland writes: "Current AI machine-learning algorithms are, at their core, dead simple stupid. They work, but they work by brute force." (p. 198.)