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12-11-2015, 14:49

Coursera - Algorithm Design & Analysis Part 2

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Coursera - Algorithm Design & Analysis Part 2
Coursera - Algorithm Design & Analysis Part 2
MP4 | AVC 76kbps | English | 960x540 | 29.97ps | 19h 04mins | AAC stereo 108kbps | 1.67 GB
Genre: Video Training

Course Syllabus:
Weeks 1 and 2: The greedy algorithm design paradigm. Applications to optimal caching and scheduling. Minimum spanning trees and applications to clustering. The union-find data structure. Optimal data compression.

Weeks 3 and 4: The dynamic programming design paradigm. Applications to the knapsack problem, sequence alignment, shortest-path routing, and optimal search trees.

Weeks 5 and 6: Intractable problems and what to do about them. NP-completeness and the P vs. NP question. Solvable special cases. Heuristics with provable performance guarantees. Local search. Exponential-time algorithms that beat brute-force search.

Recommended Background
How to program in at least one programming language (like C, Java, or Python); and familiarity with proofs, including proofs by induction and by contradiction. At Stanford, a version of this course is taken by sophomore, junior, and senior-level computer science majors. The course assumes familiarity with some of the topics from Algo 1 --- especially asymptotic analysis, basic data structures, and basic graph algorithms.
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