LPU - Lovely Professional University
What you'll learn

The Course "Crack DSA: Learn, Code, Solve" is designed to build a strong foundation in Data Structures and Algorithms through a balanced approach of theory, coding, and problem-solving and side by side building their professional profile. Students will learn core concepts such as arrays, linked lists, stacks, queues, trees, graphs, and hashing, along with fundamental algorithmic techniques like searching, sorting, and recursion. Emphasis is placed on developing logical thinking and analytical skills by solving real-world and interview-oriented problems, including curated LeetCode exercises. By the end of the course, learners will be able to design efficient solutions, analyze algorithm performance, and apply data structures effectively in programming tasks thus making them placement ready.

  • Basics of Data Structures, Classification of Data Structures (Linear and Non-linear), Abstract Data Types , Introduction to Algorithms, Time Complexity, Space Complexity, Asymptotic Notations (Big-O, Theta, Omega), Algorithmic Trade-offs
  • Array Representation in Memory, Array Traversal, Insertion and Deletion in Arrays, Linear Search, Binary Search (Iterative and Recursive), Bubble Sort, Selection Sort, Insertion Sort, Comparison of Sorting Algorithms, Problem Solving using Arrays
  • Introduction to Linked Lists, Singly Linked List, Doubly Linked List, Circular Linked List, Header Linked List, Insertion in Linked List, Deletion in Linked List, Traversal of Linked List, Applications of Linked Lists
  • Stack Concept and Operations (Push, Pop, Peek), Stack Implementation using Array and Linked List, Applications of Stack (Expression Evaluation, Infix to Postfix), Queue Concept and Operations, Simple Queue, Circular Queue, Priority Queue, Deque (Double Ended Queue), Applications of Queue
  • Recursion Basics, Recursive Problem Solving, Tower of Hanoi, Tree Terminology, Types of Trees, Binary Tree Representation, Tree Traversals (Inorder, Preorder, Postorder), Binary Search Tree (Insertion, Deletion, Searching), AVL Trees and Rotations
  • Heaps (Min Heap and Max Heap), Heap Sort, Graph Representation (Adjacency Matrix and List), Breadth First Search (BFS), Depth First Search (DFS), Shortest Path Algorithms (Dijkstra, Floyd-Warshall), Hashing, Hash Functions, Collision Resolution Techniques

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Amanpreet
Assistant Professor

She is an experienced computer science professional with over 10 years of academic expertise, specializing in Data Structures, Algorithms, and problem-solving techniques. With a strong foundation in programming and extensive involvement in guiding students through coding challenges, she bridges the gap between theoretical knowledge and practical application. Her teaching approach is beginner-friendly and problem-driven helping students build confidence by solving real-world coding problems step by step. She is passionate about creating a supportive learning environment where students not only master core DSA concepts but also sharpen their logical thinking, strengthen their coding profiles, and gain the skills required to excel in competitive exams, placements, and technical interviews preparing them to enter the tech industry with clarity and confidence.