Design & Analysis of Algorithms

In Brief: A good computer programmer has to know his algorithms — his Quicksorts and his Dijkstra'ses. But, beyond this, he has to know how — given a new problem — to pick and choose his tools, and how to mix them and come up with a new concoction: an algorithm designed to perfectly fit the problem at hand. This course attempts to take you beyond “just” being a good programmer. It attempts to make you an Algorithms Engineer.

Target Audience: All engineers and scientists interested in the science and art of computer programming. The course teaches how to think about algorithm design, so it should be very useful to computer engineers/scientists. But since we do not assume knowledge of theoretical computer science, the course is accessible to all.

• Algorithms and analysis for all standard problems — searching, sorting, graph search, order statistics and many many more.
• Algorithmic tools and strategies — greedy, dynamic, recursive, divide and conquer, brute force, backtracking, branch and bound.
• How to go about designing an algorithm for a new problem.
• Data structure design and analysis.

Prerequisites: 12^th standard mathematics. It would be beneficial if you have done at least simple programming before.

Teacher's Introduction: Udayan Kanade did his MS in Computer Science with the specialization "Optimization and Signal Processing" from Stanford. He led algorithmic development at Codito for five years, and currently works for Oneirix Labs. Udayan has taught DAA ten times, and SAA once.