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CS50 (Computer Science 50) [a] is an introductory course on computer science taught at Harvard University by David J. Malan. The on-campus version of the course is Harvard's largest class with 800 students, 102 staff, and up to 2,200 participants in their regular hackathons .
Computer programming or coding is the composition of sequences of instructions, called programs, that computers can follow to perform tasks. [1] [2] It involves designing and implementing algorithms, step-by-step specifications of procedures, by writing code in one or more programming languages.
Code Year was a free incentive Codecademy program intended to help people follow through on a New Year's Resolution to learn how to program, by introducing a new course for every week in 2012. [32] Over 450,000 people took courses in 2012, [33] [34] and Codecademy continued the program into 2013. Even though the course is still available, the ...
Lisp is the second oldest family of programming languages in use today and as such has many dialects and implementations with a wide range of difficulties. Lisp was originally created as a practical mathematical notation for computer programs, based on lambda calculus, which makes it particularly well suited for teaching theories of computing.
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 formerly used as the textbook for MIT's introductory course in computer science.
Introduction to Algorithms is a book on computer programming by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein.The book is described by its publisher as "the leading algorithms text in universities worldwide as well as the standard reference for professionals". [1]
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Computer programming – process that leads from an original formulation of a computing problem to executable computer programs. Programming involves activities such as analysis, developing understanding, generating algorithms, verification of requirements of algorithms including their correctness and resources consumption, and implementation ...
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