DSA and CP Roadmap - Part 1

Title: A complete roadmap to master DSA & CP

Many students struggle to figure out where to start and which path to follow when it comes to DSA (Data Structures & Algorithms) and competitive programming (CP). With so many resources available, it can be overwhelming. If you're a beginner or unsure of which direction to take, this roadmap is for you. By the end of this post, I promise you’ll have a clear understanding of how to begin and what steps to follow. DSA is crucial if you're aiming for software roles since many companies begin their recruitment process with DSA-based assessments.

Understanding the Difference Between DSA and CP: Before diving in, it’s important to understand the difference between Data Structures and Algorithms (DSA) and Competitive Programming (CP).

• DSA focuses on the application and implementation of data structures and algorithms. It is the foundation for problem-solving and software development.
• CP, on the other hand, emphasizes logic, mathematical reasoning, competitive attitude, and improving your problem-solving skills.

If you’re looking for a job in an SDE role or have limited time, focus on DSA. However, if you’re passionate about problem-solving, enjoy tackling complex challenges, and have the time to dive deeper, CP is for you.

Tools and Languages:

• Code Editors: VS Code, Codeblocks, Sublime
• Languages: While you can use any language (Python, Java, JavaScript), C++ is highly recommended due to its rich standard library, easy syntax, and vast resources online.

Step 1: Master the Basics of a Programming Language

Start by gaining a solid understanding of a programming language (C++ is ideal). Mastering the syntax and debugging skills will save you time later on. There are plenty of resources available online for learning C++:

• GeeksforGeeks: C++ Programming
• W3Schools: C++ Tutorial

Step 2: Understand Time and Space Complexities

Understanding Time Complexity (TC) and Space Complexity (SC) is essential for problem-solving. You’ll need to assess the efficiency of different solutions. Multiple approaches to a problem may have varying time complexities. The more efficient approach is usually the best choice.

I highly recommend checking out this YouTube playlist to master TC & SC:

• YouTube Playlist: Time and Space Complexity (Watch videos 1.5.1-1.11)

Step 3: Learn Data Structures and Practice

Next, focus on mastering key data structures in this order:

• Mathematics
• Arrays
• Strings
• Bit Manipulation
• Recursion
• Hashing
• Stacks
• Queues
• Linked Lists

For each data structure, understand its use, application, strengths, and related algorithms. Practice solving at least 20-50 problems for each data structure on platforms like LeetCode and GeeksforGeeks. Consistent practice will strengthen your problem-solving skills.

Theory and Learning Resources:

• GeeksforGeeks: Data Structures

YouTube Channels:

• Abdul Bari
• TakeUForward
• NeetCode

Solving Problems:

• LeetCode: LeetCode
• GeeksforGeeks: Practice Questions

Moving to Advanced DSA

Once you’re comfortable with basic data structures, dive into Advanced DSA topics like:

• Backtracking
• Dynamic Programming
• Trees
• Graphs
• Disjoint Set Union (DSU)
• Tries
• Segment Trees

These topics will require more time and effort, but with consistent practice, you’ll build the problem-solving skills needed for competitive programming.

In Conclusion: Following these three steps will help you build a strong foundation in DSA. Once you've mastered DSA and solved 300-400 problems, you can level up your journey by diving into CP.

In the next post, I’ll guide you on how to start the CP journey.