Improving my skills in data structures and algorithms (DSA) helped me secure interviews at Amazon, Google, and Microsoft. But let me tell you, mastering DSA was tough. I spent many hours reading books, taking courses, and tackling LeetCode problems. Looking back, I see I wasted time on methods that didn’t help. In this article, I’ll share the strategies that really worked for me. These methods helped me conquer DSA without feeling stressed. We’ll discuss key DSA topics for interviews. I’ll share useful resources and a simple guide to mastering any DSA topic from the beginning. Plus, I’ll share my revision strategy to help you remember what you learn.
Must-Know DSA Topics for Interviews
We can categorize DSA topics into three pillars:
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Data Structures:
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Linear: Arrays, Linked Lists, Stacks, Queues, Hash Tables
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Non-linear: Trees, Binary Search Trees, Heaps, Graphs, Trie, Union Find.
Start with linear data structures before tackling the more complex non-linear ones.
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Algorithms:
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Sorting: Various sorting algorithms (e.g., quicksort, mergesort).
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Searching: Binary Search.
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Bit Manipulation: Understanding bitwise operations.
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Tree Traversal: Inorder, Preorder, Postorder, Level Order.
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Graph Algorithms:
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Depth-First Search (DFS)
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Breadth-First Search (BFS)
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Topological Sort
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Shortest Path Algorithms
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Dijkstra’s
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Bellman-Ford
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Problem-Solving Techniques:
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Two Pointers
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Sliding Window
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Prefix Sum
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Fast and Slow Pointers
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Divide and Conquer
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Greedy Algorithms
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Recursion
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Backtracking
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Dynamic Programming
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Top K Elements
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Other topics, such as segment trees and Fenwick trees, come up less often in interviews. Focus on the core topics first. Understanding time and space complexity is also crucial throughout your DSA journey.
One of my biggest early mistakes was trying to juggle too many topics at once. It’s overwhelming! Focus on one topic at a time. You don’t have to be an expert before moving on. Just aim for a strong grasp of the topic’s mechanics and implementation. Also, make sure you can solve simple LeetCode problems related to it.
The Right Order to Learn DSA Topics
Remember, some topics build upon others. For instance, if you’re shaky on recursion, tree problems will be a struggle. Here’s the order I recommend:
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Linear Data Structures: Arrays, Linked Lists, Stacks, Queues, Hash Tables.
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Fundamental Algorithms and Problem-Solving Patterns include:
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Two Pointers
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Sliding Window
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Recursion
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Backtracking
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Sorting
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Searching
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Bit Manipulation
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Hierarchical Data Structures: Trees, Binary Search Trees, Trie, Heaps.
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Advanced Algorithms: Greedy Algorithms, Dynamic Programming.
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Graphs and Union Find: These are typically more complex.
How to Start Learning a New Topic
Follow these steps to effectively tackle a new DSA topic:
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Basics: Understand the concept, its code representation, common operations, and time/space complexities. For example, with Binary Search Trees, understand their structure. Also, learn how to do operations like insertion, deletion, and search.
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Real-World Applications: DSA isn’t just for interviews! Understanding their real-world uses makes learning more engaging. Use Google or ChatGPT to find out how a specific data structure or algorithm is used in real life. This adds context and motivation.
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Pen and Paper: Visualize! Use diagrams and pseudocode to understand how the algorithm or data structure works. This is invaluable for understanding linked lists, trees, and graph traversals.
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Implement From Scratch: Coding it yourself solidifies your understanding. Use arrays or linked lists to implement stacks. Create your own sorting algorithms, too. This helps you understand the underlying mechanisms better.
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Built-in Libraries: You might not create code from scratch in interviews. But, knowing how to use built-in libraries is key. Get to know Python’s lists, sets, and dictionaries. Also, learn about Java’s ArrayList, HashMap, and TreeSet.
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Solve Easy Problems: Theory isn’t enough. Practice solidifies your learning. After grasping the basics, solve 4-5 easy LeetCode problems related to the topic.
Resources to Learn DSA
You can find many great online resources to help you build a solid DSA foundation. YouTube has especially useful content.
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Abdul Bari’s Algorithm Playlist: Clear explanations of fundamental algorithms.
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William Fiset’s Data Structures and Graph Playlist: Excellent visualizations and in-depth coverage.
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Tushar Roy’s Dynamic Programming Playlist: A great resource for tackling DP.
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Coursera’s Algorithms Part 1 and 2: These courses cover many DSA topics in detail.
I’ve compiled these and many more resources in my GitHub repository: Awesome LeetCode Resources.
How to Master a DSA Topic
Once you have the basics down, it’s time to dive deeper. Here are my tips:
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Focus on Problem-Solving: Theory is important, but you learn best by solving problems. Don’t get stuck in tutorial hell. Once you understand a concept, start practicing on LeetCode.
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Challenge Yourself: Gradually increase the difficulty. Don’t just stick to easy problems. Push yourself to tackle medium and hard problems. This is how you truly grow.
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Understand, Don’t Memorize: Focus on the underlying principles. Don’t just memorize code. It’s okay to look at solutions, but understand why they work. Then, implement the solution yourself. Identify the key trick or pattern that unlocks the solution for challenging problems.
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Think in Patterns: Recognizing patterns drastically speeds up your problem-solving. As you practice, identify common techniques and group similar problems together. Some common patterns include:
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Two Pointers: Often used for array or linked list problems involving pairs or triplets.
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Sliding Window: Useful for subarray or substring problems involving fixed-size windows.
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Fast and Slow Pointers: Detecting cycles in linked lists or arrays.
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Merge Intervals: Problems involving overlapping intervals.
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Backtracking: Permutations, combinations, and exploring all possible configurations.
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How to Retain What You Have Learned
Retention is just as crucial as learning. Here’s how to make your knowledge stick:
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Repetition: Revisit challenging problems regularly. Don’t just solve them once and forget them. Make revision lists (Revision 1, Revision 2) to track your progress. This helps you revisit problems after longer gaps.
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Bookmark Everything Important: Save links to helpful resources, articles, and problem-solving guides. Organize them for easy access.
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Be Consistent: DSA mastery takes time and effort. Be patient and persistent. Even a little practice each day makes a big difference. Set realistic goals and stick to your schedule.
I hope these tips help you on your DSA journey! Remember, consistency is key. Keep practising, and you’ll master data structures and algorithms. If you enjoyed this article, please join my WhatsApp channel. I share more insights on coding, DSA, and system design there. Let me know in the comments if you’d like a detailed breakdown of any problem-solving patterns. Good luck, and happy coding.
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