This comprehensive course introduces data structures and algorithms using Python in a beginner-friendly and structured way. It is designed to help learners build strong programming foundations and prepare for coding interviews and technical assessments.

The course starts with fundamental concepts such as binary search, linear search, and algorithm complexity, including Big O notation. It then introduces core data structures like linked lists and explains how they are used in solving real programming problems.

You will also learn about binary search trees, tree traversal techniques, recursion, and how these concepts are applied in problem-solving scenarios.

The course covers hash tables and Python dictionaries, explaining how hashing works, how data is stored, and how collisions are handled. It also includes sorting algorithms and divide-and-conquer strategies to solve complex problems efficiently.

A major part of the course focuses on recursion and dynamic programming, including common problems like knapsack and optimization techniques.

In addition, the course explores graph algorithms such as breadth-first search (BFS), depth-first search (DFS), and shortest path algorithms.

Finally, it includes interview preparation tips and coding strategies to help learners approach technical interviews with confidence.

By the end of this course, learners will have a solid understanding of data structures and algorithms in Python and be well-prepared for real-world programming challenges and interviews.