Intermediate Algorithmic Techniques
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Algorithms are crucial building tools of both Computer Science and Computer Engineering. This is the second course on algorithms designed to provide students with a broader and deeper understanding on algorithm design and analysis.
Through this course, we will learn
- Additional tools for analysis of the time and space requirements of computer algorithms
- Additional algorithmic techniques.
- Additional problem areas and their algorithmic solutions.
- How to analyze recursive algorithms;
- Powerful analytical methods
- Key ideas
- Sample Applications: string matching, optimal matrix multiplications.
- Key ideas
- Sample Applications: Nearest neighbors, convex hulls.
- Key ideas: Ford-Fulkerson method,
- Sample Applications: maximum bipartite matching, additional applications.
- Key ideas: Backtracking and branch-and-bound.
- Sample applications: Knapsack and assignment problems.
Who should attend
- Professionals who wish to improve their algorithmic solutions for 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.