Coding Practice with Guided Learning Paths

If you’re in 1st or 2nd year, one of the biggest questions is — How do I start DSA? Which resource is the best? Which one should I stick to? How do I stay consistent when others around me aren’t even thinking about placements yet? I’ve been through that phase. When I started, I used the GFG DSA Self-Paced Course to build a foundation. Gradually, I began solving problems on LeetCode, giving regular contests, and learning from discussion forums. That process helped me build confidence, one step at a time. Trust me — waiting until the end of 3rd year to start placement prep can feel like trying to catch a train that’s already gone. Even solving just 1–2 problems daily can save you from a lot of rejections later on. Resources I Used: • Striver’s A2Z DSA Sheet (455 problems) – for structured and progressive practice • LeetCode & HackerRank – for daily problem-solving • GFG Interview Corner & LeetCode Discuss – to read recent interview experiences • NovoResume & Overleaf – for building a clean and professional resume Here’s the 5-Step Roadmap that kept me on track: 1. Pick the right problem sets → Start with Striver’s A2Z Sheet — it covers all core topics in the right order. 2. Learn topics step-by-step → Arrays → Strings → Sorting → Stack → Queue → Recursion → Trees → Graphs → DP 3. Solve problems daily on LeetCode → Even 2–3 quality problems daily > long breaks + burnout. 4. Join contests regularly → Learn to perform under time pressure, simulate real interview environments. 5. Take mock interviews early → Don’t wait to feel “ready.” You’ll grow faster when you step out of your comfort zone. After solving 1000+ problems, I realized most questions fall under these common patterns: ✔ Sliding Window & Two Pointers ✔ Binary Search on Answer ✔ Greedy + Sorting ✔ Kth Element using Heaps ✔ Prefix/Suffix Tricks, Tries ✔ Graph (DFS/BFS, Dijkstra, Kruskal) ✔ Tree Traversals ✔ DP Variations (Knapsack, LIS, etc.) ✔ Stack/Parenthesis problems ✔ Fast & Slow Pointers (Linked Lists) But the real growth came from: → Practicing under constraints → Taking mocks → Analyzing mistakes Start now. Start small. Stay consistent. That’s how I landed at ServiceNow — and you can too.

Reality Check for Aspiring Software Engineers: If you're not proficient in Data Structures and Algorithms (DSA), you're missing out on numerous opportunities with top tech companies. Mastering DSA is not just about cracking interviews; it's about building a solid foundation for problem-solving and efficient coding. Here's a structured path to guide you through mastering DSA: 1. Array & Hashing: → These basics will form the building blocks for more complex topics. → Recommended Problems: Frequency count, Anagram checks, Subarray sums. 2. Two Pointer & Stack: → Perfect for problems involving sequences and order management. → Recommended Problems: Pair sums, Valid parentheses, Largest rectangle in histogram. 3. Two Pointer ->Binary Search, LinkedList, Sliding Window: → Dive deeper into efficient searching with Binary Search, manage data dynamically with Linked Lists, and tackle contiguous data problems with Sliding Windows. → Recommended Problems: Search in a rotated array, Detect cycle in linked list, Longest substring without repeating characters. 4. Trees: → Understand hierarchical data structures with Trees, manage parent-child relationships efficiently. → Recommended Problems: Binary tree traversal, Lowest common ancestor. 5. Tries, Heap, Backtracking: → Level up with Tries for prefix-based searches, → Heaps for priority management, and Backtracking for exploring possibilities. → Recommended Problems: Word search, Priority queues, Sudoku solver. 6. Backtracking ->Graph, 1D & 2D DP: → Graphs are used for networked data, and Dynamic Programming (DP) → Recommended Problems: Shortest path, Knapsack problem, Unique paths in a grid. 7. Bit Manipulation: → Solve problems with efficient, low-level operations. → Recommended Problems: Single number, Subset generation using bits. 8. Intervals, Greedy, Advanced Graph: → Tackle interval problems for range-based data, use Greedy algorithms for locally optimal solutions, and explore advanced graph topics for complex networks. → Recommended Problems: Meeting rooms, Minimum number of platforms, Maximum flow. ▶️ Resources: → Online coding platforms (LeetCode, HackerRank) → Comprehensive courses (Coursera, Udemy) → Books (Cracking the Coding Interview, Introduction to Algorithms) Pro Tip: Consistent practice and understanding the underlying principles are key. Solve diverse problems and learn from each one. Stay determined, keep learning, and soon you'll be acing those coding interviews! Follow me for insights on Leadership, System Design, and Career Growth!

POV: You are BAD at DATA STRUCTURES and ALGORITHMS Because you are not learning them visually!! Here some tools that you can use 🔵 MUST-USE (Core Practice) 1. LeetCode → leetcode.com The non-negotiable. Start with the Blind 75, then NeetCode 150. Use company filters to target your dream companies specifically. 2. NeetCode.io → neetcode.io Built by a Google SWE. Curated roadmap + free YouTube video for every single problem. Best structured path I’ve seen. 🟢 VISUALIZERS (Understand Before You Code) 3. VisuAlgo → visualgo.net Watch sorting, graph traversal, tree operations animate in real time. Never code an algorithm you haven’t seen move. 4. CS USF Visualization → https://lnkd.in/gWzd63fT University of San Francisco’s tool. Best for AVL Trees, B-Trees, Red-Black Trees — structures VisuAlgo doesn’t cover. 5. Algorithm Visualizer (cVisTool) → algorithm-visualizer.org Step through code line by line while watching the visualization update. Edit the code and re-run. This one is underrated. 🟠 ROADMAPS (Structure Your Prep) 6. Striver’s A2Z DSA Sheet → takeuforward.org 455+ problems, zero to advanced, perfect for campus placements. Pair with his YouTube channel (takeUforward). 7. Roadmap.sh → https://lnkd.in/gjucwv4H Visual CS roadmap. Use it like a checklist. Find your blind spots BEFORE your interview does. 🟢 REFERENCE (When You’re Stuck) 8. GeeksForGeeks → geeksforgeeks.org Use it as an encyclopedia, not a practice platform. Best for theory lookups and company-specific archives. 9. Big-O Cheat Sheet → bigocheatsheet.com Print this. Keep it open every single practice session. Know your complexities cold before every interview. 10. CP-Algorithms (e-maxx) → cp-algorithms.com Deep-dive reference for Segment Trees, KMP, Suffix Arrays, Bridges. When hard problems demand real theory. 🟣 PATTERNS & ADVANCED 11. 14 Coding Patterns → https://lnkd.in/gEQYXmYJ Stop memorising solutions. Learn the patterns. Sliding Window, Two Pointers, Cyclic Sort, Top K Elements — 14 templates that cover 80% of interviews. 12. Codeforces → codeforces.com Weekly contests. Virtual contest mode. Upsolve everything you couldn’t finish. This is where you build speed. 13. CSES Problem Set + Handbook → cses.fi 300-problem set + a free 300-page textbook. The cleanest curated problem set that exists. Do this and hard LeetCode starts feeling manageable. 🟠 TOOLS (Your Secret Weapons) 14. Excalidraw → excalidraw.com Draw the problem BEFORE you code it. Sketch your trees, trace your graphs. Simulate the whiteboard. Every time. 15. Python Tutor → pythontutor.com Paste any recursive function. Watch the call stack build and collapse. Best debugging tool nobody talks about. Save this post. You’ll want it later. 📌 ♻️ Repost if this helped someone in your network who’s currently in placement prep.

If I start preparing for coding interviews in 2025… ✅Build a strong foundation (WEEKS 1-4) 🎯Focus on the most frequently asked topics: - Arrays: Prefix sum, sliding window problems. - Strings: Two-pointer technique, pattern matching. - Linked Lists: Reversal, cycle detection. - Stacks/Queues: Monotonic stacks, bracket problems. 🎯Resources: - Neetcode 150 for a structured problem set. - Cracking the Coding Interview: Chapters 1-4 for basics. - Take U Forward (YouTube): Great explanation for each video. - GFG: Topic-wise problems with solutions. ✅Practice Problems Strategically (WEEKS 5-12) 🎯Tackle problems in three stages: - Stage 1: Solve 50 easy problems to get comfortable. - Stage 2: Solve 75 medium problems, focusing on optimization. - Stage 3: Solve 15 hard problems if targeting FAANG. 🎯Platforms to Practice: - LeetCode: Sort by difficulty or tags (arrays, DP). and contests - HackerRank: For warm-ups and hirimg contests. ✅Master Core Algorithms and Data Structures (WEEKS 13-16) 🎯Key Focus Areas: - Binary Search: Search in rotated arrays, peak elements. - Recursion and Backtracking: Subsets, permutations, Sudoku solver. - Dynamic Programming: - Classic problems like Fibonacci, Knapsack, LIS. - Understand bottom-up and top-down approaches. - Trees and Graphs: - BFS/DFS traversal, shortest path (Dijkstra). 🎯Resources: - Neetcode Playlists: Trees, DP, and Graphs. - Tushar Roy YouTube Channel: Algorithm deep dives. - LeetCode Discussion Forums: Optimized solutions and hints. ✅Learn System Design Basics (WEEKS 17-20) 🎯What to Focus On: - Scalability: Load balancing, horizontal scaling. - Caching: Strategies like LRU cache. - Databases: SQL VS. NOSQL, partitioning, sharding. - Design Patterns: Singleton, Observer, Factory. 🎯Resources: - System Design Primer (GitHub): Beginner to advanced. - Grokking the System Design Interview: Simplified concepts. - Designing Data-Intensive Applications: Real-world system insights. ✅Mock Interviews and Communication (WEEKS 21-24) 🎯What to Do: - Pair up with peers or mentors for mock interviews. 🎯 Use platforms: - Pramp: Peer-to-peer interviews. - InterviewBit: Mock interviews with industry experts. - Record yourself solving problems and analyze ✅Behavioral Questions (ONGOING) 🎯 What to Expect: - Questions around teamwork, challenges, and problem-solving. - Example: - Tell me about a time you resolved a conflict in a team. - How do you prioritize tasks under tight deadlines? 🎯How to Prepare: - Use the STAR method: Situation, Task, Action, Result. - Focus on stories that highlight leadership, impact, and learning. - Mock practice with peers or record yourself. 🎯Resources: - Big Interview (Behavioral Prep): Comprehensive practice. - Google common behavioral interview questions. Follow Swati Jha for content related to tech interviews, coding, software engineering and career growth. 📸 For more behind-the-scenes and quick tips, connect with me on Instagram https://lnkd.in/gDHD-Q9A

🚀 How I Went From “What Is a Linked List?” to Cracking Product-Based Companies I still remember the moment I stared blankly at a coding problem, unsure what a linked list even was. Fast forward 6 months — I received offers from JP Morgan, Salesforce, Walmart , and other product-based companies. Here’s the real roadmap — no fluff, no magic — just a structured approach that actually works. 📌 Phase 1: Build the Foundation (Month 1) - Goal: Understand core data structures and basic problem-solving. - What I did: - Learned Arrays, Strings, Linked Lists, Stacks, Queues, and HashMaps. - Practiced 5–7 problems daily on platforms like HackerRank and LeetCode (Easy). - Resource used: - GeeksforGeeks DSA Tutorials - FreeCodeCamp Algorithms & Data Structures 🔁 Phase 2: Master Key Patterns (Months 2–4) I stopped solving random problems and focused on 6 core patterns that appear in 80% of interviews: 1. Sliding Window 2. Two Pointers 3. Binary Search (including rotated arrays) 4. BFS & DFS 5. Recursion → Dynamic Programming 6. Heap / Priority Queue How I practiced: - Solved at least 8–10 problems for each pattern. - Focused on LeetCode Medium questions tagged with companies like Amazon, Salesforce, Microsoft. - Practiced explaining my approach out loud (even to my wall!). 🧪 Phase 3: Build and Showcase (Month 5) I built 2 end-to-end projects that used DSA concepts: 1. Pathfinding Visualizer (BFS, DFS, Dijkstra) 2. File Organizer Tool (Hashing, Sorting, Tree Traversal) These weren’t just “to-do apps” — they demonstrated real problem-solving skills and became talking points in interviews. 🎤 Phase 4: Interview Readiness (Month 6) - Mock Interviews: Used Pramp (free) to practice with peers. - Resume Tuning: Tailored my resume with keywords from job descriptions. - Behavioral Prep: Used the STAR method with stories from college projects and internships. 🧠 Key Mindset Shifts That Helped ✅ Consistency > Intensity: 1–2 hours daily beat 8-hour weekend grinds. ✅ Patterns > Problems: Focused on recognizing, not memorizing. ✅ Progress, Not Perfection: Celebrated small wins — like solving a problem without help. 👇 What’s the #1 thing holding you back in your DSA journey right now? Lack of a clear plan? Struggling with a specific topic? Not getting interview calls? ♻️ Repost to inspire someone who’s just starting out. Let’s connect and grow together! 🌱🔥 – Umesh Kaushik #DSA #ProductBasedCompanies #CodingInterviews #TechPlacements #LeetCode