**Course Description:**

In this course design and analysis of algorithms is studied. Methodologies include: divide and conquer, dynamic programming, and greedy strategies. Their applications involve: sorting, ordering and searching, graph algorithms, geometric algorithms, mathematical (number theory, algebra and linear algebra) algorithms, and string matching algorithms.

We study algorithm analysis - worst case, average case, and amortized, with an emphasis on the close connection between the time complexity of an algorithm and the underlying data structures. We study NP-Completeness and methods of coping with intractability. Techniques

such as approximation and probabilistic algorithms are studied for handling the NP-Complete problems.

We study algorithm analysis - worst case, average case, and amortized, with an emphasis on the close connection between the time complexity of an algorithm and the underlying data structures. We study NP-Completeness and methods of coping with intractability. Techniques

such as approximation and probabilistic algorithms are studied for handling the NP-Complete problems.

**Text:**Introduction to Algorithms, Cormen, Rivest, Leiserson.**(Click below link to follow Course Videos)**

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