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Overview

Techniques for design and performance analysis of algorithms for a variety of computational problems. Asymptotic notations, bounding summations, recurrences, best-case, worst-case and average-case analysis. Design techniques: divide-and-conquer, dynamic programming and memorisation, greedy strategy, backtracking, branch-and-bound. Algorithms: sorting and order statistics, trees, graphs and flow networks, matrices, arithmetic circuits. Intractability: classes P, NP, and NP-completeness, approximation algorithms.
Study Level

Postgraduate

Offering Terms

Term 2

Campus

Kensington

Delivery Mode

Fully on-site

Indicative contact hours

4

Course Outline

To access course outline, please visit:

Fees

Pre-2019 Handbook Editions

Access past handbook editions (2018 and prior)

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