Complexity of Algorithms: Big-O Notation

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Explores practical aspects of solving parity games, including winning strategies, algorithms, complexity, determinism, and heuristic approaches.

Explores algorithm complexity, analyzing efficiency and worst-case scenarios of sorting algorithms.

Examines NP problems, graph coloring, path optimization, and computational complexity distinctions in P and NP classes.

Covers quantum algorithms, complexity classes, Grover's algorithm, and quantum information in computational complexity.

Introduces complexity classes, including P and NP, and explores examples of easy and hard problems.

Explores algorithmic complexity, comparing growth rates using Theta notation and characterizing different complexity classes.

Delves into complexity theory, focusing on the P vs NP problem and the classification of computational problems based on efficiency.

Covers the time complexity of algorithms and includes a quiz.

Explores dynamic programming for the Knapsack problem, discussing strategies, algorithms, NP-hardness, and time complexity analysis.

Explores countability and undecidable problems in the theory of computation.