LPU - Lovely Professional University
What you'll learn

Course Description: This course builds strong fundamentals in Data Structures and Algorithms with a focus on concept clarity and placement preparation. It covers core topics like arrays, linked lists, stacks, queues, trees, graphs, and sorting/searching techniques. Emphasis is on hands-on problem solving and interview-oriented coding practice. Learning Outcomes: Students will be able to understand and apply appropriate data structures to solve problems efficiently and analyze algorithm complexity. They will develop strong logical and problem-solving skills for coding interviews. By the end, students will confidently solve placement-level questions and perform well in technical interviews.

  • Introduction to arrays and their operations including traversal, insertion, deletion, and searching. Focus on time complexity and solving basic interview problems to build a strong foundation.
  • 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.

Avatar
Dr. Avinash Kaur
Professor

Dr. Avinash Kaur


Avatar
Dr. Parminder Singh
Professor & Dy. Dean

Dr. Parminder Singh