About Course

In this course students learn and practice advanced strategies for solving complex problems to generate optimal solutions. Students will explore techniques like backtracking, greedy algorithms, and dynamic programming, along with specialized data structures like tries and segment trees. They will also explore game theory, learning how to analyse strategic decision-making. Through designing solutions and exercises, students will gain practical experience in applying these strategies to solve problems where optimization is necessary.

Course Syllabus

Back Tracking:

Greedy Method:

Introduction, general method.

Dynamic Programming:

Introduction, Memoization and Tabular Methods to store the results.

Game Theory:

Tries/Pattern Matching:

Introduction to trie and its implementation, KMP.

Segment Trees:

Syllabus

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