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Explores dynamic programming through memoization and a bottom-up approach to optimize recursive algorithms.

Explores optimizing exponentiation in modular arithmetic for efficient calculations and prime number determination.

Covers the analysis of algorithm efficiency and optimizing code for faster execution.

Explores models of card shuffling, state spaces, and time complexity.

Covers the analysis of worst time complexity for algorithms and time complexity with real numbers and integers.

Explores binary search trees, covering operations, implementations, and real-world applications involving train tracks.

Explores binary search fundamentals, efficiency, and temporal complexity in algorithmic searching.

Explores algorithm complexity, time complexity estimation, Landau notations, and asymptotic behavior analysis.

Covers complexity classes, effect on computer time, tractable problems, class NP, and NP-complete problems.

Covers the analysis of quick sort, including time complexity and randomization for finding the k-th smallest number.