Understanding recursion concepts and problem-solving using recursive approaches. Covers fundamental sorting algorithms like bubble, selection, insertion, and merge sort with analysis.

Study of dynamic data structures including linked lists, stacks, and queues. Implementation and applications such as reversing lists, balanced parentheses, and queue operations.

Introduction to data structures, complexity analysis, and array operations including traversal, insertion, deletion, and basic problem solving

Understanding recursion fundamentals and implementation of common sorting algorithms such as bubble, selection, insertion, and merge sort.

Concepts and implementation of linked lists, stack and queue operations, and related problem-solving techniques.

Binary trees, traversals, binary search trees, heaps, and their applications in efficient problem solving.

Graph representations, BFS, DFS, and introduction to dynamic programming concepts and patterns.

Advanced problem-solving, interview-level questions, real-world applications, and mini project implementation for placement readiness.

Introduction to tree data structures including binary trees and binary search trees. Covers traversals, heap structures, and priority queues with problem-solving applications.

Covers graph representations and traversal techniques like BFS and DFS. Introduction to dynamic programming concepts to solve optimization problems efficiently.

Focus on advanced problem-solving techniques, hashing, and real-world applications. Includes mini-projects and mock interview practice for placement readiness.