This course is designed to help learners master the core concepts of Data Structures and Algorithms (DSA) using the C programming language. Starting from the basics and advancing to complex topics like graphs, dynamic programming, and memory optimization, this course is ideal for students, job seekers, and aspiring developers. You’ll learn how to structure and manipulate data efficiently, solve real-world coding problems, and prepare for technical interviews at top companies. The content is structured step-by-step, combining theory with hands-on coding examples and practice problems to reinforce understanding. Whether you're preparing for university exams, campus placements, or competitive programming, this course provides a strong foundation in logic building, code efficiency, and problem-solving using C. Key Highlights: Covers all major DSA topics from beginner to advanced level 100+ coding examples with explanations Focus on time and space complexity optimization Designed for coding interviews, competitive exams, and CS fundamentals
Data Structures and Algorithms (DSA) form the backbone of computer science and software development. Mastering DSA equips you to solve complex problems efficiently — which is why it's a top priority in interviews, projects, and real-world systems.
A Data Structure is a special format for organizing and storing data so that it can be accessed and modified effectively. The right choice of data structure can drastically improve your program's performance.
An Algorithm is a step-by-step procedure to solve a problem or perform a task. In programming, algorithms are paired with the right data structures to achieve optimal results.
| Algorithm | Best Case | Average Case | Worst Case | Stable? |
|---|---|---|---|---|
| Bubble Sort | O(n) | O(n²) | O(n²) | Yes |
| Quick Sort | O(n log n) | O(n log n) | O(n²) | No |
| Merge Sort | O(n log n) | O(n log n) | O(n log n) | Yes |
Just like a mechanic uses different tools for different tasks, a programmer chooses specific algorithms and data structures based on the problem at hand.
Don’t just memorize code — understand the problem it solves. Practice implementation and dry-run your logic. Visit UdaanPath.com for practice sets and quizzes.
In the next chapter, we’ll explore Time and Space Complexity — how to measure the performance of your programs.
