Computational complexity is the amount of resources required to run an algorithm, which is typically expressed as a function of the size of the input. Analysis of algorithms and complexity theory are related, as the complexity of an algorithm is an upper bound on the complexity of the problem it solves. Time and space complexity are usually expressed in terms of the number of elementary operations and memory storage requirements respectively.
Carnegie Mellon University
Fall 2022
A course offering rigorous study of computation, examining the central results and questions about the nature of computation, including finite automata, computational complexity, and cryptography.
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+ 10 more conceptsStanford University
Autumn 2022-2023
Stanford's CS 221 course teaches foundational principles and practical implementation of AI systems. It covers machine learning, game playing, constraint satisfaction, graphical models, and logic. A rigorous course requiring solid foundational skills in programming, math, and probability.
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+ 88 more conceptsUniversity of Washington
Summer 2022
This course is a continuation of CSE 142, focusing on manipulating data, implementing data structures, and learning about algorithms in Java. It delves into abstract data types, recursion, inheritance, and more.
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+ 34 more concepts