Programming Languages›Data Structures and Algorithms (DSA)

Master Data Structures & Algorithms — Build Strong Foundations for Coding and Interviews!

⭐ 4.8/5👩‍🎓 15,204+ students

Learn how to think like a programmer and solve complex problems efficiently. This DSA course covers every essential concept — arrays, linked lists, stacks, queues, trees, graphs, recursion, dynamic programming, and more — all taught through real coding examples and challenges.

About This Course

The DSA course by Urbancode focuses on practical understanding and problem-solving. You’ll master core data structures, algorithmic techniques, and pattern-based problem-solving used in coding interviews. Each module includes coding exercises, mock tests, and real-world challenges designed to prepare you for competitive programming and top-tier tech placements.

Data Structures and Algorithms (DSA)
  • Hours of Instructor-Led Training
  • Hands-on Projects across Web, Data & AI
  • Includes Beginner → Expert Level Topics
  • Mentor Support, Assignments & Code Reviews
  • Job Assistance & Portfolio Guidance
  • Urbancode Certificate of Completion

What You'll Learn

Master Core DSA Concepts

Understand how data structures and algorithms work under the hood.

Improve Problem-Solving Skills

Solve 100+ real-world problems to build strong analytical thinking.

Crack Technical Interviews

Get interview-ready with pattern-based coding questions and mock tests.

Learn Multiple Languages

Practice DSA in C++, Java, or Python with language-specific examples.

Understand Algorithmic Efficiency

Analyze and optimize your code using time and space complexity.

Capstone Problem Solving

Apply all concepts in advanced projects and algorithmic challenges.

Course Content

  • Introduction to programming and logic building
  • Understanding time and space complexity
  • Big O notation and performance analysis
  • Recursion fundamentals
  • Mathematical problems and patterns

  • 1D and 2D arrays
  • Common array problems and optimizations
  • String manipulation and pattern matching
  • Sliding window and two-pointer techniques

  • Singly and doubly linked lists
  • Fast and slow pointer approaches
  • Stack operations and implementation
  • Applications of stacks (parsing, evaluation, etc.)

  • Queue and circular queue implementation
  • Priority queues and Deque
  • Hash tables and hash maps
  • Collision handling and optimization