LPU - Lovely Professional University
What you'll learn

This final module is all about bringing everything together. It’s where your understanding of Data Structures and Algorithms (DSA) meets the real world. You’ll take on advanced problems and work on hands-on projects that challenge you to apply what you’ve learned—whether it’s recursion, dynamic programming, trees, graphs, or hashing. The focus isn’t just on getting the right answer, but on writing clean, efficient, and fast code that can hold up under pressure - just like in interviews or real-world software projects. Think of this as your DSA capstone—where you level up from learning to building, solving, and creating. By the end of this course, you’ll be confident in solving complex DSA problems using techniques like backtracking, graph traversal, and dynamic programming. You’ll know how to choose and apply the right data structures—like heaps, stacks, queues, or hash maps - to tackle real challenges. Your code will be not only correct but clean, optimized, and ready for time-bound situations. Most importantly, you’ll build complete projects that bring together all these skills - showing that you can think critically, solve problems creatively, and turn your DSA knowledge into real, working solutions.

  • Introduction to DSA, Time & Space Complexity Arrays – Basics, Operations (Insert, Delete, Search), Sorting (Bubble, Selection, Insertion), Searching (Binary Search, Two-Pointer, Sliding Window), Advanced Problems & Practice
  • Singly Linked List – Implementation & Operations, Doubly and Circular Linked List, Recursion – Basics, Backtracking, Advanced Problems & Practice
  • Stack – Implementation, Applications (Infix to Postfix, Next Greater Element), Queue – Implementation, Types (Circular Queue, Priority Queue), Hashing – Hash Tables, Collision Handling, Hashing – Applications (Frequency Count, LRU Cache), Practice Day – Stack, Queue, and Hashing Problems
  • Binary Trees – Basics, Traversals (Inorder, Preorder, Postorder), Binary Trees – Advanced (Diameter, LCA, View Problems), Binary Search Tree (BST) – Operations, Problems, Heaps – Min Heap, Max Heap, Heap Sort, Advanced Problems & Practice
  • Graphs – Representation, BFS, DFS, Graphs – Topological Sort, Cycle Detection Shortest Path Algorithms (Dijkstra, Floyd Warshall) Dynamic Programming (Basics, Knapsack) DP – Advanced Problems (LCS, LIS)
  • Advanced Problems & Practice, Solve real-world problems with a time limit, Projects
  • Introduction to DSA, Time & Space Complexity Arrays – Basics, Operations (Insert, Delete, Search), Sorting (Bubble, Selection, Insertion), Searching (Binary Search, Two-Pointer), Practice Problems
  • Singly Linked List – Implementation & Operations, Doubly and Circular Linked List, Recursion – Basics, Backtracking, Practice Problems
  • Stack – Implementation, Applications Queue – Implementation, Types (Circular Queue, Priority Queue), Hashing – Hash Tables, Collision Handling, Hashing – Applications (Frequency Count, LRU Cache), Practice Day – Stack, Queue, and Hashing Problems
  • Binary Trees – Basics, Traversals (Inorder, Preorder, Postorder), Binary Search Tree (BST) – Operations, Problems, Heaps – Min Heap, Max Heap, Heap Sort, Advanced Problems & Practice
  • Graphs – Representation, BFS, DFS, Graphs – Topological Sort, Cycle Detection Shortest Path Algorithms (Dijkstra, Floyd Warshall)
  • Advanced Problems & Practice, Solve real-world problems with a time limit, Projects

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Mukesh Sharma
Assistant Professor

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