Coding Interview Resources

If you're a software engineer in your 20s, beware of this habit, it can kill your growth faster than anything else. ► Fake learning. It feels productive, but it's not. Let me give you a great example: You wake up fired up. Open YouTube, start a system design video. An hour goes by. You nod, you get it (or so you think). You switch to a course on Spring Boot. Build a to-do app. Then read a blog on Kafka. Scroll through a thread on Redis. By evening, you feel like you’ve had a productive day. But two weeks later? You can’t recall a single implementation detail. You haven’t written a line of code around those topics. You just consumed, but never applied. That’s fake learning. It’s learning without doing. It gives you the illusion of growth, while keeping you stuck. 📌 Here’s how to fix it: Watch fewer tutorials. Build more things. Learn with a goal: “I’ll use this to build X.” After every video, write your own summary. Recode it from scratch. Start documenting what you really understood vs. what felt easy. Real growth happens when you struggle. When you break things. When you debug. Passive learning is comfortable. But discomfort is where the actual skills are built. Your 20s are for laying that solid technical foundation. Don’t waste them just “watching smart.” Build. Ship. Reflect. That’s how you grow.

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Working under a bad tech lead can slow you down in your career, even if you are the most talented Here’s what you should do if you're stuck with a bad tech lead: Ineffective Tech Lead: - downplays the contributions of their team - creates deadlines without talking to the team - views team members as a tool to build and code - doesn’t trust their team members to do their jobs - gives no space or opportunities for personal / skill development Effective Tech lead: - sets a clear vision and direction - communicates with the team & sets realistic goals - empowers you to make decisions and take ownership - inspires and helps you achieve your career milestones - always looks to add value by sharing their knowledge and coaching I've always grown the most when I've worked with the latter. But I also have experience working with the former. If you are in a team with a bad tech lead, it’s tough, I understand. Here’s what you can do: ➥don’t waste your energy worrying about them ➥focus on your growth and what you can do in the environment ➥focus and try to fill the gap your lead has created by their behaviors ➥talk to your manager and share how you're feeling rather than complain about the lead ➥try and understand why they are behaving the way they behave, what’s important for them And the most important: Don’t get sucked into this behavior and become like one! You will face both types of people in your career: Some will teach you how to do things, and others will teach you how not to do things!

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Coding Interviews Roadmap 👆

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If I wanted to get my opportunity to interview at Google or Amazon for SDE roles in the next 6-8 months… Here’s exactly how I’d approach it (I’ve taught this to 100s of students and followed it myself to land interviews at 3+ FAANGs): ► Step 1: Learn to Code (from scratch, even if you’re from non-CS background) I helped my sister go from zero coding knowledge (she studied Biology and Electrical Engineering) to landing a job at Microsoft. We started with: - A simple programming language (C++, Java, Python — pick one) - FreeCodeCamp on YouTube for beginner-friendly lectures - Key rule: Don’t just watch. Code along with the video line by line. Time required: 30–40 days to get good with loops, conditions, syntax. ► Step 2: Start with DSA before jumping to development Why? - 90% of tech interviews in top companies focus on Data Structures & Algorithms - You’ll need time to master it, so start early. Start with: - Arrays → Linked List → Stacks → Queues - You can follow the DSA videos on my channel. - Practice while learning is a must. ► Step 3: Follow a smart topic order Once you’re done with basics, follow this path: 1. Searching & Sorting 2. Recursion & Backtracking 3. Greedy 4. Sliding Window & Two Pointers 5. Trees & Graphs 6. Dynamic Programming 7. Tries, Heaps, and Union Find Make revision notes as you go — note down how you solved each question, what tricks worked, and how you optimized it. ► Step 4: Start giving contests (don’t wait till you’re “ready”) Most students wait to “finish DSA” before attempting contests. That’s a huge mistake. Contests teach you: - Time management under pressure - Handling edge cases - Thinking fast Platforms: LeetCode Weekly/ Biweekly, Codeforces, AtCoder, etc. And after every contest, do upsolving — solve the questions you couldn’t during the contest. ► Step 5: Revise smart Create a “Revision Sheet” with 100 key problems you’ve solved and want to reattempt. Every 2-3 weeks, pick problems randomly and solve again without seeing solutions. This trains your recall + improves your clarity. Coding Projects:👇 https://whatsapp.com/channel/0029VazkxJ62UPB7OQhBE502 ENJOY LEARNING 👍👍

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9 tips to prepare for coding interviews: Master DSA fundamentals (arrays, strings, trees, graphs) Practice daily on LeetCode, Codeforces, or HackerRank Solve problems under time constraints Review commonly asked interview patterns Mock interviews help reduce anxiety Understand the “why” behind each solution Prepare clean, structured explanations Brush up on system design and OOP basics Stay consistent — prep a little every day Coding Interview Resources:👇 https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X ENJOY LEARNING 👍👍

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9 tips to get better at system design: Understand scalability: vertical vs horizontal Learn how load balancers distribute traffic Know how caching improves performance Study database types: SQL vs NoSQL Design with failure in mind (redundancy & backups) Understand APIs and how services communicate Focus on real-world use cases (URL shortener, chat app) Think about latency, throughput, and consistency Always start with a high-level diagram before diving deep

what programming language do you use most often 🌟

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🔰 Data Manipulation with Arrays

Data manipulation with arrays is commonly used in real-life scenarios such as processing and analyzing large datasets in scientific research, financial analysis, and business intelligence applications.

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9 tips to get better at debugging code: Read error messages carefully — they often tell you everything Use print/log statements to trace code execution Check one small part at a time Reproduce the bug consistently Use a debugger to step through code line by line Compare working vs broken code Check for typos, null values, and off-by-one errors Rubber duck debugging — explain your code out loud Take breaks — fresh eyes spot bugs faster Coding Interview Resources:👇 https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X ENJOY LEARNING 👍👍