This is an in-depth course designed to instill foundational and advanced knowledge of sorting and searching algorithms. The course navigates through various types and functionality of these algorithms, their complexity analysis, and practical application in solving complex coding problems.

This course dives into the understanding and application of basic data structures including Linked Lists, Stacks, and Queues. It sheds light on the inner workings of these structures, their implementation, time, and space complexity, along with their effectiveness in solving interview-focused algorithmic coding challenges.

This course is designed to provide a deep understanding of trees in Python with a specific focus on binary trees, binary search trees, and heaps. The course covers the BFS and DFS in non-binary trees to elaborate on the different traversal methods. It extensively draws attention to the use of tree data structures in solving complex interview problems.

This course is designed to demonstrate the representation of a graph using adjacency graphs and adjacency matrices in Python. A core part of the course is dedicated to implementing and utilizing BFS and DFS algorithms in graphs. Explore the comprehensive use of graph data structures in solving intricate interview-based algorithmic problems.