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[Udacity] Introduction to Graduate Algorithms

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What you’ll learn

Dynamic Programming
Randomized Algorithms
Divide and Conquer
Graph Algorithms
Max-Movement Issues
Linear Programming
NP-Completeness

Requirements

College students are anticipated to have an undergraduate course on the design and evaluation of algorithms. Specifically, they need to be conversant in primary graph algorithms, together with DFS, BFS, and Dijkstra’s shortest path algorithm, and primary dynamic programming and divide and conquer algorithms (together with fixing recurrences). An undergraduate course in discrete arithmetic is assumed, and college students must be comfy analyzing the asymptotic operating time of algorithms.

Description

This can be a graduate-level course within the design and evaluation of algorithms. We examine strategies for the design of algorithms (akin to dynamic programming) and algorithms for basic issues (akin to quick Fourier remodel or FFT).

As well as, we examine computational intractability, particularly, the idea of NP-completeness. The principle matters lined within the course embody: dynamic programming; divide and conquer, together with FFT; randomized algorithms, together with RSA cryptosystem and hashing utilizing Bloom filters; graph algorithms; max-flow algorithms; linear programming; and NP-completeness.

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