Advanced Algorithmic Techniques With Applications
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The theory of algorithms is an important foundation of both Computer Science and Computer Engineering. This is a third course on algorithms to provide students with additional algorithmic techniques and expose them to the theory of computational complexity, which offers a deeper understanding of the demarcation between hard and easy problems.
Through this course, we will learn
- Additional algorithmic techniques.
- Additional problem areas and their algorithmic solutions.
- Lower bounds and the theory of computational complexity
Hard Problems and Complexity Theory
- Key ideas: Decision and optimization problems, P and NP, NP-completeness and reductions
- Sample Applications
Approximation Algorithms and Heuristics
- Key ideas: Heuristic vs approximation algorithms.
- Sample Applications: Set covering, TSP, scheduling.
- Key ideas: Monte Carlo and Las Vegas algorithms.
- Sample Applications: Hashing and Bloom filters
Introduction to Lower Bounds
- Key ideas: Lower bound theory
- Sample Applications: searching, sorting, etc.
Who should attend
Professionals who wish to further improve their algorithmic techniques for solving non-trivial problems. School teachers who wish to refresh the concepts about algorithms; - Any one with intellectual curiosity about computing and wishes to improve problem solving techniques.