This course provides a structured introduction to core computer science concepts using Data Structures and Algorithms. It is designed to help learners understand how algorithms are analyzed, designed, and optimized for real-world problem solving.

The course begins with an overview of algorithms and their importance in computing. You will learn how to evaluate performance using analysis techniques that help measure efficiency and scalability.

Next, the course covers asymptotic notations, which are used to describe how algorithms behave as input size grows. This includes understanding best-case, worst-case, and average-case performance.

A major part of the course focuses on divide and conquer strategies, where complex problems are broken into smaller subproblems and solved efficiently. You will also explore linear-time sorting algorithms that improve performance over basic sorting methods.

The course introduces essential data structures and explains how they are used to organize and process data efficiently. You will also study binary search trees, which are widely used for fast searching and sorting operations.

Finally, the course covers dynamic programming, a powerful technique for solving complex problems by breaking them into overlapping subproblems.

By the end of this course, you will have