18 episodes

In this graduate class, UC Davis computer science professor Charles Martel describes advanced methods for the design and analysis of algorithms. He applies these techniques to design fast solutions for a wide range of applications including scheduling, network routing, computational biology, resource management and network design.  The techniques studied include dynamic programming, network flows  and randomized algorithms. The class also studies how to classify problems as hard via np-completeness theory and how to deal with hard problems using approximation algorithms, special cases, and search techniques.

Design and Analysis of Algorithms (Fall, 2008) UC Davis

    • Technology
    • 3.7, 3 Ratings

In this graduate class, UC Davis computer science professor Charles Martel describes advanced methods for the design and analysis of algorithms. He applies these techniques to design fast solutions for a wide range of applications including scheduling, network routing, computational biology, resource management and network design.  The techniques studied include dynamic programming, network flows  and randomized algorithms. The class also studies how to classify problems as hard via np-completeness theory and how to deal with hard problems using approximation algorithms, special cases, and search techniques.

Customer Reviews

3.7 out of 5
3 Ratings

3 Ratings

FotchyX ,

Useful and Accessible Lectures

Cohesive and logical follow up to the undergraduate algorithms class. These lectures will not teach you how to program exactly, but they will scaffold how you can think about algorithms at a high level and problem solve with computers.

Based on my experience, you'll be better equipped to evaluate and learn from the many, many resources scattered online. There's a flood of data structures and algorithms available, so it helps to know the main categories, problem types, and tools to evaluate them in practice.

Good luck and happy coding!

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