Andras Tornai

🚨 𝐓𝐡𝐞 𝐌𝐨𝐬𝐭 𝐔𝐧𝐭𝐨𝐮𝐜𝐡𝐞𝐝 𝐀𝐬𝐩𝐞𝐜𝐭 𝐨𝐟 𝐂𝐨𝐝𝐢𝐧𝐠 𝐏𝐥𝐚𝐜𝐞𝐦𝐞𝐧𝐭𝐬: 𝐀𝐩𝐭𝐢𝐭𝐮𝐝𝐞! 🚨 When preparing for placements, most students focus heavily on DSA and technical skills. But there’s one critical area that often gets ignored—𝐀𝐩𝐭𝐢𝐭𝐮𝐝𝐞. Many colleges don’t teach it, and yet it’s the 𝐟𝐢𝐫𝐬𝐭 𝐡𝐮𝐫𝐝𝐥𝐞 in placement rounds for many companies, both for service-based and product based. 🧠 𝐇𝐞𝐫𝐞’𝐬 𝐭𝐡𝐞 𝐭𝐡𝐢𝐧𝐠: No matter how much you’ve practiced DSA, if you’re not prepared for the aptitude round, you might not even get to showcase your coding skills. So many students miss out on further rounds because they neglect aptitude. 𝐌𝐲 𝐬𝐮𝐠𝐠𝐞𝐬𝐭𝐢𝐨𝐧: While preparing for your placements, dedicate time to 𝐚𝐩𝐭𝐢𝐭𝐮𝐝𝐞 𝐩𝐫𝐚𝐜𝐭𝐢𝐜𝐞. It’s not hard—it’s mostly math from 𝐜𝐥𝐚𝐬𝐬 6,7 𝐚𝐧𝐝 8—but the challenge is 𝐬𝐩𝐞𝐞𝐝 𝐚𝐧𝐝 𝐚𝐜𝐜𝐮𝐫𝐚𝐜𝐲. A lot of 𝐬𝐭𝐚𝐫𝐭𝐮𝐩𝐬 skip the aptitude round, but 𝐬𝐞𝐫𝐯𝐢𝐜𝐞-𝐛𝐚𝐬𝐞𝐝 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 and some 𝐩𝐫𝐨𝐝𝐮𝐜𝐭 𝐛𝐚𝐬𝐞𝐝 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 rely on it heavily. 🔑 𝐖𝐡𝐚𝐭 𝐜𝐚𝐧 𝐲𝐨𝐮 𝐝𝐨?: - Start learning some aptitude tricks from 𝐘𝐨𝐮𝐓𝐮𝐛𝐞—there are plenty of free resources. - Practice regularly to build your 𝐬𝐩𝐞𝐞𝐝 𝐚𝐧𝐝 𝐜𝐨𝐧𝐟𝐢𝐝𝐞𝐧𝐜𝐞. - Focus on topics like 𝐛𝐚𝐬𝐢𝐜 𝐦𝐚𝐭𝐡, 𝐥𝐨𝐠𝐢𝐜𝐚𝐥 𝐫𝐞𝐚𝐬𝐨𝐧𝐢𝐧𝐠, 𝐚𝐧𝐝 𝐯𝐞𝐫𝐛𝐚𝐥 𝐚𝐛𝐢𝐥𝐢𝐭𝐲. Aptitude isn’t a 𝐡𝐚𝐫𝐝-𝐚𝐧𝐝-𝐟𝐚𝐬𝐭 𝐫𝐮𝐥𝐞—it’s about applying simple concepts quickly. If you prepare for it, you’ll stand out in your placements and move smoothly through the rounds. Don’t let this overlooked segment stop you from landing your dream job. 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐞 𝐧𝐨𝐰 𝐚𝐧𝐝 𝐭𝐡𝐚𝐧𝐤 𝐦𝐞 𝐥𝐚𝐭𝐞𝐫! 😊 Follow Harshit Luthra for more #Aptitude #CodingPlacements #CareerAdvice #ServiceBasedCompanies #PlacementTips #JobSeekerAdvice #StudentGuidance #PreparationIsKey

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🚀 Day 40 Update: Solving "Last Stone Weight" and "Minimize the Sum" in DSA Practice! 🚀 Today marks the fortieth day of my DSA practice journey, and I focused on solving two specific problems: "Last Stone Weight" and "Minimize the Sum". Here's a summary of my progress: 🔍 Problem 1: "Last Stone Weight" Task: Given an array of stone weights, repeatedly smash the two heaviest stones together. The remaining stone will be the absolute difference between them. Repeat the process until only one stone remains or no stones are left. Solution: Used a max heap (priority queue) to efficiently get the heaviest stones at each step. By smashing the two heaviest stones and pushing the result back into the heap, I simulated the smashing process until only one stone remains or there are none. 🔍 Problem 2: "Minimize the Sum" Task: Given an array of numbers, perform operations to minimize the sum of the array. 🌟 Achievements: Successfully solved the "Last Stone Weight" problem using a max heap, enhancing my understanding of heap operations and how to apply them in real-world scenarios. 💪💡 #DSAChallenge #Day40 #HeapProblems #ProblemSolving

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DSA - Week 11- Progress 😊🪔✨...... 1. Introduction to Bit manipulation ✅ 2. Binary number conversion ✅ 3. 1's and 2's complement ✅ 4. Operators ✅ 5. Swap two numbers ✅ 6. Extract the ith bit ✅ 7. Set the ith bit ✅ 8. Toggle the ith bit ✅ 9. Check if power of 2 ✅ 10. Count the set bits ✅ 11. Minimum bit flips to convert number ✅ 12. Single number 1 ✅ 13. Single number 2 ✅ 14. Single number 3 ✅ 15. Xor of number in a given range ✅ 16. Divide two numbers without division operators ✅ #dsa #algorithms #mathematics #application #thinking #logic

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🌟 Day 39 of the 45-60 Days DSA Challenge 🌟 I could only manage to solve one problem today as I was busy preparing for my internals: 1. Insert Delete GetRandom O(1) - Duplicates Allowed Balancing studies and coding is tough, but I’ll keep moving forward! 💪 Arsh Goyal #DSAChallenge #Day39 #ProblemSolving #BalancingStudies #KeepGoing #CodingJourney #CrackYourInternship #CrackYourPlacement

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#Day22 DSA (Priya Bhatia )(Raghav Garg ) Question covered =>count pairs whose sum is less than target WebDevelopment (Anurag Singh ) #CSS -Position Static -Position Relative in Depth -Top Property with Relative Position -Bottom Property with Relative Position - Left Property with Relative Position -Inset Property with Relative Position -Unset Value of Relative Property 🔻Position property of each element is static(by default), we can set it relative or absolute or sticky or fixed. 🔻inset ⇒ it includes all 4 (top, bottom, left , right) 🔻unset ⇒ it will change the position to static #css #html #javascript #dsa #algorithms #datastructure #frontend #coding #developer #consistency #learnings #staymotivated #techjourney #leetcode #dailyquestions #connections #web #webdevelopmeny #bennett #bennetian #codeeveryday

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MY FIRST EVER LINKEDIN POST!!!! -> Well yeah in a sense it's first ever Competitive Programming post! -> I have recently begun to take CP seriously and giving contests! -> I wasn't feeling good about my performance until yesterday so I didn't post any in this field. -> BUTTTTT, yesterday's summer round from EPIC Institute of Technology was wonderful!!! -> The second question took thinking and I solved it. -> 3rd I left it and tried the 4th one for 1hr 30min but couldn't crack it! -> This boosted some confidence in me that even I can get better!!! I thank: Vishwa Mohan Sir: For introducing competitive programming in the first semester. Deepak Kumar Gour Sir: My mentor throughout this journey, who introduced me to Codeforces. Abhijith S sir: For laying the foundation of C language, enabling my switch to C++. All my college professors Md Imran A, Anurag Tiwari, Syed Zabi Ulla for their support and motivation. I forgot to mention the competitive programmers who push me to strive for hard ones: Vivek Gupta, Abhishek Saini, Deepak Kumar Gour Sir, Abhinav Awasthi, Aryan C., Gaurish Baliga, and Priyansh Agarwal #CompetitiveProgramming #Codeforces

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🚀 Day 4 of My 45-Day DSA Challenge! 🚀 Hey everyone! 👋 I'm back with another update on my 45-day challenge inspired by Arsh Goyal. Today, I worked on a mix of Linked List, Array, and Permutation problems. 🌟 🔍 Problems Solved Today: Palindrome Linked List Add Binary Palindrome Number Ceiling in Sorted Array Permutations in Array Permutations in Two Arrays such that the Sum of Corresponding Elements is Greater than k 💻 GitHub Repository: You can find all my solutions here(https://lnkd.in/da6Z4UfG): GitHub Repository. Check them out and share your feedback! A huge shoutout to Arsh Goyal for the inspiration. Let's keep pushing forward and crack those internships together! 💪 #45DayChallenge #DSA #CodingJourney #ProblemSolving #LearningEveryday #GitHub #Coding #Programming #CrackYourInternship Arsh Goyal

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🌟 Day 3 of the 45-60 Days DSA Challenge 🌟 Today, I managed to solve two problems: 1. Merge Sorted Array 2. Majority Element Honestly, it was a tough day for me. I didn’t perform as well as I know I can, but setbacks are a part of the process. I’m determined to bounce back stronger and give my best in the upcoming days. 💪 Arsh Goyal Looking forward to pushing through and making steady progress! #DSAChallenge #Day3 #ProblemSolving #CodingJourney #Perseverance #GrowthMindset #CrackYourInternship #CrackYourPlacement

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90% of your life problems will go away if you solve the problem of being inconsistent for yourself. You already know what to do, but you don’t do it because you’re inconsistent. Inconsistent with studying → lack of focus Inconsistent with daily exercise → lack of good health Inconsistent with doing DSA → lack of strong fundamentals Inconsistent with sleeping well → lack of peace in your mind Inconsistent with time management → lack of respect for yourself Inconsistent with eating healthy food → lack of energy during the day And we could go on… We all have big ideas, dreams, and goals to achieve, but only 1-3% make it big. Why? Because we fail to do anything about our goals. Because we don’t have the patience and focus to do the same boring thing daily. You can procrastinate, regret and repeat this cycle or decide to break it. I know this sounds harsh and rude, but it’s the reality. Being consistent doesn’t mean you need to have 100% energy daily. You just need to show up and repeat, and you will get used to it. So, it depends on you. Keep starting again after 1-2 days or mark it day 1 today and don’t fall back. 

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#100daysofcode Day 43 Of 100Daysofcode💻 Today I Solved 3 Problems On GeeksforGeeks and Leetcode✨ •Count number of bits to be flipped to convert A to B •Find the number that appears odd number of times •Power Set(Bit Manipulation) #CodeChallenge #GeeksforGeeks #ProblemSolving #leetcode #strivers

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🚀 Weekly Contest 425 Update Participated in LeetCode's Weekly Contest 425 and solved 2 out of 4 problems, securing a global rank of 8276. 🌟 🔑 Problem 1: Minimum Positive Subarray Sum Approach: Used Sliding window algorithm but initially included negative sums, leading to one wrong submission. This cost me 5 minutes of penalty time. Adjusted the logic and got the solution accepted! 💪 🔑 Problem 2: Rearrange k Substrings to Form Target Substring Approach: Created frequency maps for k-length substrings of both strings. If the maps matched, rearrangement was possible. Successfully solved this one. ✔️ 🔑 Problem 3: Tried a heap-based approach but couldn't handle all edge cases, leading to failure on some test cases. 🔑 Problem 4: Attempted a graph-based approach but got stuck at certain points. Every challenge adds to the learning curve. Onward to the next one! 🚀 #LeetCode #ProblemSolving #WeeklyContest #CodingJourney #KeepLearning

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🚀 DSA on MONDAY! Get ready to ace your next interview with these 40 most asked DSA questions! Here’s your roadmap to success: ➤ Arrays and Strings: Find the maximum sum subarray. Find all substrings that are palindromes. Implement the "two sum" problem. Implement Kadane's algorithm for maximum subarray sum. Find the missing number in an array of integers. Merge two sorted arrays into one sorted array. Check if a string is a palindrome. Find the first non-repeating character in a string. Write a program to remove duplicates from a sorted array. ➤ Linked Lists: Reverse a linked list. Detect a cycle in a linked list. Find the middle of a linked list. Merge two sorted linked lists. Implement a stack using a linked list. Find the intersection point of two linked lists. ➤ Stacks and Queues: Implement a stack using an array. Implement a stack that supports push, pop, top, and retrieving the minimum element. Implement a circular queue. Design a max stack that supports push, pop, top, and retrieve the maximum element. Design a queue using stacks. ➤ Trees and Binary Search Trees: Find the height of a binary tree. Find the lowest common ancestor of two nodes in a binary tree. Validate if a binary tree is a valid binary search tree. Serialize and deserialize a binary tree. Implement an inorder traversal of a binary tree. Find the diameter of a binary tree. Convert a binary tree to its mirror tree. ➤ Graphs: Implement depth-first search (DFS). Implement breadth-first search (BFS). Find the shortest path between two nodes in an unweighted graph. Detect a cycle in an undirected graph using DFS. Check if a graph is bipartite. Find the number of connected components in an undirected graph. Find bridges in a graph. ➤ Sorting and Searching: Implement bubble, insertion, selection, and merge sort. Implement quicksort. Implement binary search. Implement interpolation search. Find the kth smallest element in an array. Count the number of inversions in an array (an inversion occurs when two elements are out of order). 🔍 But wait, there's more! Next week, we’ll dive into Dynamic Programming (DP), Backtracking, Hashing, Heaps, Tries, and Greedy Algorithms. Get ready to sharpen your problem-solving skills and master DSA! 💪 #DSA #InterviewPreparation #CodingInterview #DataStructures #Algorithms #TechInterviews #ProblemSolving #CareerGrowth #LearnToCode #TechSkills

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🎉 Day 91/125 of #125DaysOfCoding 🚀 Today, I tackled the "First Negative in every Window of Size N" problem on GeeksForGeeks! 🔍💼 This challenge required me to efficiently navigate sliding windows to identify the first negative number in each window of size N. 🧩 By maintaining a queue to track the positions of negative numbers, I was able to swiftly determine the correct outputs for each window. 🚀 This problem sharpened my ability to work with data streams and optimize algorithms. Excited to keep growing with each challenge! 💪 #CodingJourney #GeeksForGeeks #KeepLearning #CodingChallenge #ProblemSolving 💻

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Hello LinkedIn Fam! 👋 Welcome to Day 4 of my DSA Journey! 🎯 🔥 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝗱 𝗧𝗼𝗽𝗶𝗰 𝗼𝗳 𝘁𝗵𝗲 𝗗𝗮𝘆: Binary Search Binary Search is one of the most efficient search algorithms for sorted arrays. Instead of checking each element, it divides the array into halves and determines whether the target element lies in the left or right half, cutting down the search space drastically. 🔍 How it works: Start by comparing the middle element of the array to the target. If it matches, return the index. If the target is smaller, focus on the left half; if larger, focus on the right half. Repeat the process until the element is found or the search space is exhausted. ⏱️ Time Complexity: Best case: O(1) Worst case: O(log n) 💾 Space Complexity: O(1) Binary Search is highly efficient for large datasets, making it an essential tool in your programming toolkit. Remember, the array must be sorted for Binary Search to work! Stay tuned for more insights, tips, and examples! #BinarySearch #Algorithms #DSA #Java #TimeComplexity #EfficientSearching #FullStackDevelopment #coding #linkedin

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Today I solved N-Queens problem. It's a LC-hard problem based on Backtracking and Array. Surprisingly, I did it in only one submission 💀(taken 42 min). I'm not so much into DSA but still my problem solving is okay. I'm doing everything except CP. If you haven't solved it, I'd recommend to jump into it. It's really a good problem. PS: Comment down what you are doing currently. #java #dsa #problemsolving #backtracking #array

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Hey LinkedIn fam! 👋 🚀#geeksforgeeks #potd problem of the day today!💻✨ GfG Problem:Minimize the Heights I Link:https://lnkd.in/g_ZXf_qG Problem statement: Given a positive integer k and an array arr[] denoting heights of towers, you have to modify the height of each tower either by increasing or decreasing them by k only once. Find out what could be the possible minimum difference of the height of shortest and longest towers after you have modified each tower. Note: A slight modification of the problem can be found here. Examples: Input: k = 2, arr[] = [1, 5, 8, 10] Output: 5 Explanation: The array can be modified as [3, 3, 6, 8]. The difference between the largest and the smallest is 8 - 3 = 5. Constraints 1 ≤ k ≤ 104 1 ≤ number of towers ≤ 105 0 ≤ arr[i] ≤ 105 #geekstreak2024

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Day 71/100 of learning web development and Dsa Managing both development and dsa is tough and we often get confused 🥲 though throughout these days i was focusing more on development and less on dsa and after researching today now i will shift my focus and i will do dsa first then development. We all learn from mistakes and with time so do i. So from now i be doing onky Dsa and a very little development its a long journey we cabt achieve everything in 100 days or 200 days be disciplined and keep working hard. What did you learn today? The learning journey continues! Stay tuned for more updates as I go through the remaining journey. 🌐 If you're on a similar path or have tips to share, let's connect and inspire each other! 🤝. . . . . . . . . . . #coderarmy #coding #codingchallenge #codingjourney #dsachallenge #dsa #webdevelopment #fullstack #mern #mernstack #cpp #cplusplus #arrays #100daysofcodechallenge

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