LPU - Lovely Professional University
What you'll learn

Introduces the fundamental concepts of data structures and their role in efficient problem solving. It covers the design, implementation, and analysis of various data structures such as arrays, linked lists, stacks, queues, trees, and graphs. The course also focuses on algorithm efficiency, complexity analysis, and practical applications of data structures in real-world computing problems. Students will learn how to choose appropriate data structures to optimize performance.

  • Introduction to Data Structures and Algorithms, importance in problem solving, and basic understanding of time and space complexity.
  • Study of Big-O, Big-Theta, and Big-Omega notations to evaluate algorithm efficiency.
  • Understanding array structure, memory allocation, traversal, insertion, deletion, and updating elements.
  • Implementation of linear and binary search along with solving array-based problems.
  • Concepts of doubly and circular linked lists and their advantages over singly linked lists.
  • Practical implementation of linked lists using programming constructs.
  • Applications of stack such as expression evaluation, parentheses matching, and recursion.
  • Introduction to binary trees, structure, properties, and basic operations.
  • Inorder, preorder, and postorder traversal techniques for binary trees.
  • Concept of recursion, base and recursive cases, and solving problems recursively.
  • Introduction to dynamic programming, overlapping subproblems, and optimal substructure.

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Richa Sharma
Assistant Professor

Richa Sharma is a Software Engineer and DSA expert with extensive experience expertise lies in demystifying complex algorithms and data structures for aspiring developers. She has a proven track record of mentoring students to succeed in technical interviews and competitive programming


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Dr. Aarti
Professor

Dr. Aarti is an educator with over 10 years of experience teaching Data Structures and Algorithms. She specializes in helping learners understand complex concepts in a simple, clear, and practical way. She has strong expertise in core DSA topics, including arrays, linked lists, stacks, queues, trees, graphs, and algorithm design. Her teaching emphasizes hands-on practice and problem-solving so that students can confidently apply their knowledge to real-world and technical challenges. She believes that learning Data Structures and Algorithms is not just about writing code, but about developing strong logical thinking, problem-solving abilities, and an analytical mindset essential for real-life applications and career growth.