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 and Operations (Insert, Delete, Search), Arrays – Sorting (Bubble, Selection, Insertion), Searching (Binary Search, Two-Pointer, etc.), and Arrays – Practice Problems.
  • Linked Lists : Introduction, Memory representation, Allocation, Traversal, Insertion, Deletion, Header linked lists: Two-way lists: operations on two way linked lists
  • Stacks : Introduction: List and Array representations, Operations on stack (traversal, push and pop), Queue : Array and list representation, operations (traversal, insertion and deletion), Priority Queues
  • Hashing – Hash Tables, Collision Handling, Hashing – Applications (Frequency Count, LRU Cache), Heaps – Min Heap, Max Heap, Heap Sort, and Practice Problems - Hashing and heap.
  • Binary Trees – Introduction (Complete and Extended Binary Trees), Memory Representation (Linked, Sequential), Binary Search Tree – Introduction, Searching, Insertion and Deletion, Traversing, and Practice Problems.
  • Graph Traversal – BFS, DFS, Graphs – Topological Sort, and Cycle Detection

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Mukesh Sharma
Assistant Professor

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Arvind Kumar
Assistant Professor

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