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  2. CS50 - Wikipedia

    en.wikipedia.org/wiki/CS50

    CS32 (Computational Thinking and Problem Solving), taught by Michael D. Smith, [29] is an alternative to CS50 but does not have a free online version. [30] The next course in sequence after CS32 or CS50 is CS51: Abstraction and Design in Computation, instructed by Stuart M. Shieber with Brian Yu as co-instructor. [31]

  3. Competitive programming - Wikipedia

    en.wikipedia.org/wiki/Competitive_programming

    A programming competition generally involves the host presenting a set of logical or mathematical problems, also known as puzzles or challenges, to the contestants (who can vary in number from tens or even hundreds to several thousand). Contestants are required to write computer programs capable of solving these problems. Judging is based ...

  4. David J. Malan - Wikipedia

    en.wikipedia.org/wiki/David_J._Malan

    David Jay Malan (/ m eɪ l ɛ n /) is an American computer scientist and professor. Malan is Gordon McKay Professor of Computer Science at Harvard University, and is best known for teaching the course CS50, [2] [3] which is the largest open-learning course at Harvard University and Yale University and the largest massive open online course at EdX, with lectures being viewed by over a million ...

  5. SAT solver - Wikipedia

    en.wikipedia.org/wiki/SAT_solver

    In computer science and formal methods, a SAT solver is a computer program which aims to solve the Boolean satisfiability problem.On input a formula over Boolean variables, such as "(x or y) and (x or not y)", a SAT solver outputs whether the formula is satisfiable, meaning that there are possible values of x and y which make the formula true, or unsatisfiable, meaning that there are no such ...

  6. HiGHS optimization solver - Wikipedia

    en.wikipedia.org/wiki/HiGHS_optimization_solver

    Written in C++ and published under an MIT license, HiGHS provides programming interfaces to C, Python, Julia, Rust, JavaScript, Fortran, and C#. It has no external dependencies. A convenient thin wrapper to Python is available via the highspy PyPI package. Although generally single-threaded, some solver components can utilize multi-core ...

  7. Constrained optimization - Wikipedia

    en.wikipedia.org/wiki/Constrained_optimization

    After the problem on variables +, …, is solved, its optimal cost can be used as an upper bound while solving the other problems, In particular, the cost estimate of a solution having x i + 1 , … , x n {\displaystyle x_{i+1},\ldots ,x_{n}} as unassigned variables is added to the cost that derives from the evaluated variables.

  8. AOL Mail

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    Get AOL Mail for FREE! Manage your email like never before with travel, photo & document views. Personalize your inbox with themes & tabs. You've Got Mail!

  9. Constraint satisfaction problem - Wikipedia

    en.wikipedia.org/wiki/Constraint_satisfaction...

    Constraint satisfaction problems (CSPs) are mathematical questions defined as a set of objects whose state must satisfy a number of constraints or limitations. CSPs represent the entities in a problem as a homogeneous collection of finite constraints over variables , which is solved by constraint satisfaction methods.

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    solving problems set0 cs50 python code book for beginners pdf version free