Algorithms in Computer Science: Search and Sort Techniques

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Covers worst-case complexity, algorithms, and proofs including mathematical induction and recursion.

Explains the merge sort algorithm, its correctness, and time complexity compared to other sorting algorithms.

Explores dynamic programming for palindromic subsequences, merging binary search trees, and finding the median of two sorted arrays.

Introduces selection and insertion sorting algorithms, explaining their correctness and time complexity.

Explores worst-case complexity, mathematical induction, and algorithms like binary search and insertion sort.

Introduces the CS-250 Algorithms course, covering its structure, objectives, and key topics in algorithmic problem-solving.

Covers the complexity analyses of algorithms and their worst-case time complexities.

Explores optimization problems and greedy algorithms for efficient decision-making.

Discusses matrix multiplication using divide-and-conquer techniques and introduces Strassen's algorithm for improved efficiency.

Covers hashing, sorting, extendible hashing, linear hashing, and external sorting.