Paras Khandelwal’s Post

Most people struggle with DSA not because they aren't smart, but because they lack a structured roadmap. They jump from Hard problems to Easy ones without mastering the fundamentals. I've compiled a 75-Day LeetCode Challenge that breaks down the 75 most impactful questions into 10 core patterns: Arrays & Strings - The foundation of logic. Linked Lists & Stacks - Mastering memory and flow. Binary Search & Trees - Optimized searching. DP & Graphs - Cracking the MAANG-level rounds. Each problem comes with a clean C++ solution and the logic behind it. Whether you are prepping for your first internship or a Senior Dev role at a top-tier tech firm, this is the only checklist you need. Inside this guide: 75 Curated Questions. Optimized code implementations. Strategic category breakdown (Arrays, Strings, Trees, and more). Found this pdf helpful? 1. Follow me Rahul kumar for more Al & Tech career resources. 2. Like this post. 3. Comment "READY" Let's stop the aimless scrolling and start the targeted solving. #LeetCode #CodingInterview #Software Engineering #DSA #CareerGrowth #TechInterview #Programming #PersonalBranding

Most people struggle with DSA not because they aren't smart, but because they lack a structured roadmap. They jump from Hard problems to Easy ones without mastering the fundamentals. I’ve compiled a 75-Day LeetCode Challenge that breaks down the 75 most impactful questions into 10 core patterns: ✅ Arrays & Strings – The foundation of logic. ✅ Linked Lists & Stacks – Mastering memory and flow. ✅ Binary Search & Trees – Optimized searching. ✅ DP & Graphs – Cracking the MAANG-level rounds. Each problem comes with a clean C++ solution and the logic behind it. Whether you are prepping for your first internship or a Senior Dev role at a top-tier tech firm, this is the only checklist you need. Inside this guide: • 75 Curated Questions. • Optimized code implementations. • Strategic category breakdown (Arrays, •• Strings, Trees, and more). Found this pdf helpful? 1. Follow me Dinesh Sahu for more AI & Tech career resources. 2. Like this post. 3. Comment "READY" Let’s stop the aimless scrolling and start the targeted solving. #LeetCode #CodingInterview #SoftwareEngineering #DSA #CareerGrowth #TechInterview #Programming #PersonalBranding

I needed RateMyProfessors data for a side project and discovered there's no public API — so I reverse-engineered their GraphQL endpoints and built one myself. That turned into a full open-source API client, now available in both Python and TypeScript, published on PyPI and npm. Just shipped v3.0.0. What it does: • Search and retrieve professor & school data • Paginate through ratings with built-in cursor support • Fully typed, with automatic retries and rate limiting out of the box Already at almost 3k downloads across both packages and growing. If you're building anything that needs professor or university rating data, give it a try — and if you find it useful, a ⭐ on GitHub goes a long way. 🐍 PyPI: https://lnkd.in/eA2FRcfX 📦 npm: https://lnkd.in/enPzBsmz 💻 GitHub: https://lnkd.in/eF6Zbvbe

Most interns wait for instructions. Professionals bring solutions. 🚀 If you’re a CS student, 'knowing how to code' is just the baseline. To get that return offer, you need to be "Day-One Productive." 3 tips to level up before your first day: 1️⃣ Master the PR Review: Don't just submit code. Learn to read others' code, spot edge cases, and give constructive feedback. Be a team player. 2️⃣ Debugging > Coding: Anyone can follow a tutorial. Can you use a debugger and read stack traces? That’s real engineering. 3️⃣ Document the 'Why': Senior devs care WHY you chose a specific logic. Document your architectural decisions. At KodeMaster AI, we don't just teach syntax. Our project-based paths simulate your first week on the job: IDE, Git, and real feedback. 💻 Ready to bridge the gap? What’s the #1 skill you’re working on this summer? Let’s hear it below! 👇 #CodingTips #JuniorDev #CareerAdvice #KodeMasterAI #CSStudents #SoftwareEngineering

Day 72/120: Competitive Execution, Product Safety, and the Academic Baseline. The pipeline is at maximum capacity. Balancing active enterprise production, nationwide coding gauntlets, and university exams requires strict resource allocation. -> Algorithmic & Competitive Execution: Officially cleared Round 1 of HackWithInfy (Infosys), a nationwide DSA competitive programming gauntlet. The 120-day daily execution metric is translating directly into high-pressure competitive results. Backed this up by solving 'Rotting Oranges' on LeetCode—engineering a Multi-Source Breadth-First Search (BFS) to model state mutation across a matrix. Resolved the simulation in strict O(N×M) time, securing a 0ms runtime. -> Enterprise Execution (Univ.live): Pushed production code targeting core platform stability. Resolved several foundational infrastructure issues and spearheaded the development of a critical safety feature for the live product. Writing algorithms is the baseline; writing code that directly protects the end-user is the actual standard of production engineering. -> Academic Delivery: Maintained the academic execution metric. Finalized technical presentations (PPTs) and continued heavy theoretical preparation for my ongoing university exams in modern computing architectures. Clear the gauntlet. Protect the user. Master the theory. #120DaysOfCode #HackWithInfy #SoftwareEngineering #GraphAlgorithms #Internship #DevOps #LeetCode #Cpp

I published a research paper while still in college — here’s what I learned. In my final year at MGM College, we built InterPlacement — a full-stack placement platform: • Job posts & student applications • Live video interviews via Zegocloud • AI chatbot (Gemini) for student queries • Auto offer/rejection emails based on candidate fit • Video stored on Firebase Storage, images on Cloudinary We published our research paper in MAT Journals (March 2025). Key lessons: Build full products → integration breaks first → ship to learn → clarity matters in architecture. #BuildInPublic #FullStack #SpringBoot #React #TechCareers #Java

𝐋𝐞𝐦𝐦𝐞 𝐬𝐡𝐚𝐫𝐞 𝐰𝐢𝐭𝐡 𝐲𝐨𝐮 𝐬𝐨𝐦𝐞𝐭𝐡𝐢𝐧𝐠 What my CS degree taught me: → Linked lists and binary trees (never touched them again) → How to write assembly language (why) → The history of programming languages nobody uses anymore → Theoretical OS concepts on a 2009 textbook → How to draw ER diagrams by hand in an exam → Dijkstra's algorithm (memorized it, forgot it, Googled it later anyway) What my first software engineering job asked me on day 1: → Do you know Git? → Have you ever worked in an Agile team? → Can you read someone else's messy code without crying? → Do you know how to Google an error message properly? → Have you ever deployed anything in your life? 4 years of CS. And honestly? Most of my real skills came from random YouTube videos, internships, and one senior colleague who actually took time to explain things. I am not saying education is useless. I am saying the gap between what we study and what we actually need is embarrassingly wide. And we have known this for years. Nobody has fixed it yet. Well what's the most useless thing you studied that you have never used once in real life? 👇 #SoftwareEngineering #CSGraduate #Programming #Developer #TechCareers #CodingLife #ComputerScience #Pakistan

𝐈𝐟 𝐲𝐨𝐮’𝐫𝐞 𝐚 1𝐬𝐭 𝐲𝐞𝐚𝐫 𝐂𝐒 𝐬𝐭𝐮𝐝𝐞𝐧𝐭, 𝐫𝐞𝐚𝐝 𝐭𝐡𝐢𝐬 𝐛𝐞𝐟𝐨𝐫𝐞 𝐢𝐭’𝐬 𝐭𝐨𝐨 𝐥𝐚𝐭𝐞. Most students spend years just “coding”… without understanding what level they’re actually at. Here’s the difference 👇 • Programmer Focus: Writing code → Learns syntax, solves basic problems, builds logic • Software Developer Focus: Building applications → Uses frameworks, creates projects, works with real users • Software Engineer Focus: Designing systems → Thinks about scalability, architecture, performance, and long-term impact What 1st year students should actually do: • Master programming fundamentals (Python, DSA, problem-solving) • Start building small real projects (web apps, AI mini-projects) • Learn how systems work (APIs, databases, basic architecture) • Don’t just copy code — understand why it works Reality check: Your goal isn’t to stay a coder. Your goal is to become a software engineer who can design systems. ➕ Follow Esha Tariq for more #SoftwareEngineering #ComputerScience #Programming #FirstYear #TechCareers #LearnToCode #Developers #AI #DSA #Students #CareerGrowth

There’s a gap most students don’t realize until it’s too late. They practice Data Structures & Algorithms extensively, but struggle when asked to apply those concepts in real systems. That’s the difference between preparation and readiness. Projects like distributed rate limiters, caching systems, or real-time aggregators aren’t just impressive- they signal something deeper: the ability to think in systems, trade-offs, and scalability. Recruiters aren’t just evaluating problem-solving. They’re evaluating how you translate that thinking into real-world applications. If your learning stops at solving questions, you’re missing the layer that actually gets you hired. The shift is simple: from solving → to building. Explore projects that push your thinking beyond syntax. Learn from FREE resources on CipherSchools: https://lnkd.in/gMcVmeQ7 #cipherschools #SoftwareEngineering #DataStructures #SystemDesign #TechCareers #EngineeringStudents #DSA #internshipprep

Day 80/120: Enterprise Internal Tooling, System Validation, and Graph Optimization. 80 days of continuous execution. The momentum is officially locked into enterprise production and architectural validation. -> Academic Validation: Successfully presented my Docker-based Remote Code Execution (RCE) project (NexusIDE) for the official university minor project evaluation. Securing top-tier feedback validates the core objective: translating complex system constraints (Containerization, WebSockets, CRDTs) into a production-ready, defensible architecture. -> Enterprise Execution (Univ.live): Shifted focus to internal platform scalability. Architected and engineered core modules for the enterprise admin panel. Building consumer-facing features is the baseline; building the secure, internal tooling that governs the platform's data flow is the backbone of production engineering. -> Algorithmic Execution: Solved 'Number of Provinces'. Engineered a Depth-First Search (DFS) to isolate and count connected components within a network. Initially converted the adjacency matrix into a dynamic adjacency list, but actively optimizing the logic to traverse the matrix directly—eliminating redundant data structures and dropping the memory overhead to a strict O(V) auxiliary space. Validate the system. Build the internal tools. Optimize the graph. #120DaysOfCode #SoftwareEngineering #SystemDesign #Docker #Internship #LeetCode #Cpp #BackendArchitecture