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📊 Data Structures & Algorithms

Master the fundamental building blocks of computer science through comprehensive study of data structures and algorithmic problem-solving techniques.

🎯 Course Overview

This comprehensive course covers essential data structures and algorithms that form the backbone of computer science and software development.

  • Duration: 16 weeks (4 credit hours)
  • Prerequisites: Basic programming knowledge
  • Languages: Python, C++, Java
  • Level: Undergraduate/Graduate
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📚 Course Content

Comprehensive curriculum covering all major data structures and algorithmic paradigms:

  • Arrays, Strings, and Basic Operations
  • Linked Lists (Singly, Doubly, Circular)
  • Stacks, Queues, and Deques
  • Trees and Binary Search Trees
  • Heaps and Priority Queues
  • Hash Tables and Hash Functions
  • Graphs and Graph Algorithms
  • Dynamic Programming
  • Greedy Algorithms
  • Complexity Analysis

🛠️ Practical Learning

Hands-on laboratory sessions and programming assignments:

  • Lab 1: Arrays and Searching Algorithms
  • Lab 2: Linked Lists Implementation
  • Lab 3: Stack and Queue Operations
  • Lab 4: Binary Tree Traversals
  • Lab 5: Hash Table Implementation
  • Lab 6: Graph Algorithms (BFS, DFS)

🎯 Learning Outcomes

Upon completion, students will be able to:

  • Implement fundamental data structures from scratch
  • Analyze time and space complexity using Big O notation
  • Choose appropriate data structures for specific problems
  • Design efficient algorithms for common computational problems
  • Apply dynamic programming and greedy techniques
  • Solve complex programming challenges

📊 Assessment Methods

Comprehensive evaluation through multiple components:

  • Laboratory Work (30%): Hands-on implementation
  • Assignments (25%): Problem-solving exercises
  • Mid-term Exam (20%): Theoretical concepts
  • Final Exam (25%): Comprehensive assessment

🌟 Career Applications

Essential skills for various tech career paths:

  • Software Development Engineer
  • Data Scientist and Analyst
  • System Design Engineer
  • Competitive Programming
  • Research and Development
  • Technical Interview Preparation
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UNIVERSITY OF DELHI SYLLABUS

📘 Course Curriculum

Unit-wise syllabus aligned with the University of Delhi curriculum.

Unit 1: Introduction and Arrays →

  • Abstract data types
  • Algorithm complexity analysis
  • Arrays and their operations

Unit 2: Linked Lists →

  • Singly linked lists
  • Doubly and circular linked lists
  • Insertion, deletion and traversal

Unit 3: Stacks and Queues →

  • Stack ADT and applications
  • Queues and circular queues
  • Expression evaluation

Unit 4: Trees →

  • Binary trees and traversals
  • Binary search trees
  • AVL trees and heaps

Unit 5: Graphs, Searching and Sorting →

  • Graph representation
  • BFS and DFS
  • Searching, sorting and hashing