Coding Interview Resources

Hi Everyone 👋, I have brought you Great Opportunity Today 𝐋𝐞𝐚𝐫𝐧 𝐂𝐨𝐝𝐢𝐧𝐠 𝐅𝐫𝐨𝐦 𝐒𝐜𝐫𝐚𝐭𝐜𝐡😍 | Get Placed In Top Tech Companies 8 Days Of Demo Classes By Industry Experts  Enhance your career with industry-relevant skills in: * Data Analytics/Data Science & AI * Cybersecurity * Full Stack Development Eligibility: BE/BTech / BCA / BSc / MCA 🌟 Trusted by 7000+ Students 🤝 450+ Hiring Partners 💼 Avg. Rs. 7.2 LPA 🚀 41 LPA Highest Package 𝐑𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐍𝐨𝐰 👇:- https://bit.ly/3AQRTRN 🎯 Don’t miss out! Limited seats are available. 🌟

10 Ways to Speed Up Your Python Code 1. List Comprehensions numbers = [x**2 for x in range(100000) if x % 2 == 0] instead of numbers = [] for x in range(100000):     if x % 2 == 0:         numbers.append(x**2) 2. Use the Built-In Functions Many of Python’s built-in functions are written in C, which makes them much faster than a pure python solution. 3. Function Calls Are Expensive Function calls are expensive in Python. While it is often good practice to separate code into functions, there are times where you should be cautious about calling functions from inside of a loop. It is better to iterate inside a function than to iterate and call a function each iteration. 4. Lazy Module Importing If you want to use the time.sleep() function in your code, you don't necessarily need to import the entire time package. Instead, you can just do from time import sleep and avoid the overhead of loading basically everything. 5. Take Advantage of Numpy Numpy is a highly optimized library built with C. It is almost always faster to offload complex math to Numpy rather than relying on the Python interpreter. 6. Try Multiprocessing Multiprocessing can bring large performance increases to a Python script, but it can be difficult to implement properly compared to other methods mentioned in this post. 7. Be Careful with Bulky Libraries One of the advantages Python has over other programming languages is the rich selection of third-party libraries available to developers. But, what we may not always consider is the size of the library we are using as a dependency, which could actually decrease the performance of your Python code. 8. Avoid Global Variables Python is slightly faster at retrieving local variables than global ones. It is simply best to avoid global variables when possible. 9. Try Multiple Solutions Being able to solve a problem in multiple ways is nice. But, there is often a solution that is faster than the rest and sometimes it comes down to just using a different method or data structure. 10. Think About Your Data Structures Searching a dictionary or set is insanely fast, but lists take time proportional to the length of the list. However, sets and dictionaries do not maintain order. If you care about the order of your data, you can’t make use of dictionaries or sets.

Master DSA in 160 days 👇👇 https://gfgcdn.com/tu/TX9/ This is a very good course by Geekforgeeks, designed for freshers to help them crack coding interviews. The best part about such courses is it helps you build consistency and discipline—two key habits that not only make DSA easier but also set you up for long-term success in your career. Like if you need similar FREE resources in the channel ENJOY LEARNING 👍👍

Coding is tricky. Coding in interviews feels even harder. It’s intimidating, uncertain and hard to prepare. Here are 4 ways to do it! 1. Interview Cake: I think it is some of the best prep available and it is targeted toward weaknesses many data scientists have in algorithms and data structures: https://www.interviewcake.com/ 2. Leetcode: While developed for software engineering interviews, it has a LOT of useful content for learning algorithms. For data science, I'd suggest focusing on Easy/Medium: https://leetcode.com/ 3. Cracking the Coding Interview: Amazing book, sometimes referred to as CTCI. A classic and one you should have: https://cin.ufpe.br/~fbma/Crack/Cracking%20the%20Coding%20Interview%20189%20Programming%20Questions%20and%20Solutions.pdf 4. Daily Coding Problem: The book and the website are awesome. Work on a daily problem. This was my go to resource for when I was looking to stay sharp: https://www.dailycodingproblem.com/ #coding

𝐅𝐫𝐞𝐞 𝐎𝐧𝐥𝐢𝐧𝐞 𝐌𝐚𝐬𝐭𝐞𝐫𝐜𝐥𝐚𝐬𝐬 : 𝐁𝐮𝐢𝐥𝐝 𝐘𝐨𝐮𝐫 𝐂𝐚𝐫𝐞𝐞𝐫 𝐢𝐧 𝐀𝐈 & 𝐌𝐋😍 Join us to explore the roadmap to becoming a successful AI & ML engineer! 🌟 𝐖𝐡𝐚𝐭 𝐘𝐨𝐮’𝐥𝐥 𝐆𝐚𝐢𝐧:- -   Insights into AI & ML career paths. - Expert guidance to kickstart your journey. Eligibility:- Students, Freshers, and Working Professionals. 📅 Date: 20th November 2024 ⏰ Time: 7:00 PM IST 🎯 𝐋𝐢𝐦𝐢𝐭𝐞𝐝 𝐒𝐞𝐚𝐭𝐬! 𝐑𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐟𝐨𝐫 𝐅𝐑𝐄𝐄👇:- https://bit.ly/3AOP9oc Start your AI & ML journey today! 🚀

Preparing for a Java developer interview can be a bit overwhelming, but breaking it down by difficulty and experience level can make it more manageable. Whether you're a fresher or an experienced developer, here's a guide to help you focus your preparation and walk into your interview with confidence. 𝗙𝗼𝗿 𝗔𝗹𝗹 𝗟𝗲𝘃𝗲𝗹𝘀 (𝗜𝗻𝗰𝗹𝘂𝗱𝗶𝗻𝗴 𝗙𝗿𝗲𝘀𝗵𝗲𝗿𝘀) ➤ Topic 1: Project Flow and Architecture (Medium) - These questions are designed to gauge your understanding of project development, teamwork, and problem-solving. Be ready to discuss a project you've worked on, including the tech stack used, the challenges you faced, and how you overcame them. 𝗙𝗼𝗿 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀 𝘄𝗶𝘁𝗵 𝗖𝗼𝗿𝗲 𝗝𝗮𝘃𝗮 𝗦𝗸𝗶𝗹𝗹𝘀 (𝟭-𝟯 𝗬𝗲𝗮𝗿𝘀 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲) ➤ Topic 2: Core Java (Medium to Hard) - Fundamental Java concepts. You'll likely face questions on strings, object-oriented programming (OOP), collections, exception handling, and multithreading. 𝗙𝗼𝗿 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲𝗱 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀 (𝟯+ 𝗬𝗲𝗮𝗿𝘀 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲) ➤ Topic 3: Java 8/11/17 Features (Hard) - This is where the interview gets more challenging. You'll asked advanced features introduced in recent Java versions, such as lambda expressions, functional interfaces, the Stream API, and modules. ➤ Topic 4: Spring Framework, Spring Boot, Microservices, and REST API (Hard) - Expect questions on popular frameworks and backend development architectures. Be prepared to explain concepts like dependency injection, Spring MVC, and microservices. 𝗙𝗼𝗿 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀 𝘄𝗶𝘁𝗵 𝗗𝗮𝘁𝗮𝗯𝗮𝘀𝗲 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 ➤ Topic 5: Hibernate/Spring Data JPA/Database (Hard) - This section focuses on data persistence with JPA and working with relational (SQL) or NoSQL databases. Be ready to discuss JPA repositories, entity relationships, and complex querying techniques. 𝗙𝗼𝗿 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀 𝘄𝗶𝘁𝗵 𝗔𝗱𝗱𝗶𝘁𝗶𝗼𝗻𝗮𝗹 𝗦𝗸𝗶𝗹𝗹𝘀 ➤ Topic 6: Coding (Medium to Hard) - You'll likely encounter coding challenges related to data structures and algorithms (DSA), as well as using the Java Stream API. ➤ Topic 7: DevOps Questions on Deployment Tools (Advanced) - These questions are often posed by managers or leads, especially if you're applying for a role that involves DevOps. Be prepared to discuss deployment tools like Jenkins, Kubernetes, and cloud platforms. ➤ Topic 8: Best Practices (Medium) - Interviewers may ask about design patterns like Singletons, Factories, or Observers to see how well you write clean, reusable code. I have curated the best resource to learn Java 👇👇 https://topmate.io/analyst/1166617 All the best 👍👍

𝐓𝐨𝐩 𝐌𝐍𝐂𝐬 𝐇𝐢𝐫𝐢𝐧𝐠😍 Roles:- Data Analyst, Data Scientist, Data Engineer &Software Developer Openings:- 100+  Qualification:- Graduate  Salary :- 6 To 25LPA 𝐔𝐩𝐥𝐨𝐚𝐝 𝐘𝐨𝐮𝐫 𝐑𝐞𝐬𝐮𝐦𝐞 👇:-   https://bit.ly/47FVWg1 Select the company name, and role and apply to the job Once you get shortlisted, you will receive a call from HR

Preparing for an Interview? Interviews can feel nerve-wracking, but with the right preparation, you can walk in feeling confident and ready to impress. Here’s a 10-step checklist to ensure you're all set: 📌Research the Company: Understand its values, culture, and recent news. This shows you're genuinely interested. 📌Know the Job Role: Be clear on the job description and how your skills match. 📌Prepare Your Answers: Practice responses to common interview questions, like "Tell me about yourself" or "What are your strengths?" 📌Dress the Part: Choose professional attire that suits the company culture. 📌Bring Copies of Your Resume: Even if the interviewer has a copy, having one ready shows you're organized. 📌Know Your Resume Inside Out: Be ready to discuss your experiences, achievements, and gaps in your employment history. 📌Prepare Questions to Ask: Asking insightful questions shows you're engaged and have done your homework. 📌Practice Good Body Language: Make eye contact, sit up straight, and offer a firm handshake. 📌Be On Time: Arriving 10-15 minutes early shows punctuality and respect. 📌Stay Calm and Positive: Stay relaxed, speak clearly, and showcase your enthusiasm for the role. Follow this checklist, and you’ll be all set to ace your interview! Top Coding Interview Resources to prepare for Microsoft, Amazon, Meta, Apple, Adobe, VMware, Visa, Twitter, LinkedIn, JP Morgan, Goldman Sachs, Oracle and Walmart 👇👇 https://topmate.io/coding/951517 All the best 👍👍

Geekforgeeks is currently running an amazing coding challenge for freshers & college students I would highly recommend you to register for this free contest if you wonna improve your DSA & Problem Solving Challenge 👇👇 https://gfgcdn.com/tu/TX9/ They're also giving away free gifts to participants ENJOY LEARNING 👍👍

When you're studying DSA, you probably think, "This won't be directly used in the actual work of a company, so why am I even doing this?" And in life, where will this even come in handy? Well, it won't be useful directly, but the hard work you're putting in—sitting day and night solving questions—that habit of working hard will pay off. It's not really about DSA, but about the effort you're willing to give that will decide which company you land your internship or placement in ❤️

30-Day Roadmap to Learn Android App Development up to an Intermediate Level Week 1: Setting the Foundation *Day 1-2:* - Familiarize yourself with the basics of Android development and set up Android Studio. - Create a simple "Hello, Android!" app and run it on an emulator or a physical device. *Day 3-4:* - Understand the Android project structure and layout files (XML). - Explore activities and their lifecycle in Android. *Day 5-7:* - Dive into user interface components like buttons, text views, and layouts. - Build a basic interactive app with user input. Week 2: Functionality and Navigation *Day 8-9:* - Study how to handle button clicks and user interactions. - Learn about intents and navigation between activities. *Day 10-12:* - Explore fragments for modular UI components. - Understand how to pass data between activities and fragments. *Day 13-14:* - Practice creating and using custom views. - Build a small project involving multiple activities and fragments. Week 3: Data Management *Day 15-17:* - Learn about data storage options: SharedPreferences and internal storage. - Understand how to work with SQLite databases in Android. *Day 18-19:* - Study content providers and how to share data between apps. - Practice implementing data persistence in a project. *Day 20-21:* - Explore background processing and AsyncTask for handling long-running tasks. - Understand the basics of threading and handling concurrency. Week 4: Advanced Topics *Day 22-23:* - Dive into handling permissions in Android apps. - Work on projects involving file operations and reading/writing to external storage. *Day 24-26:* - Learn about services and background processing. - Explore broadcast receivers and how to respond to system-wide events. *Day 27-28:* - Study advanced UI components like RecyclerView for efficient list displays. - Explore Android's networking capabilities and make API requests. *Day 29-30:* - Delve into more advanced topics like dependency injection (e.g., Dagger). - Explore additional libraries and frameworks relevant to your interests (e.g., Retrofit for networking, Room for database management). - Work on a complex project that combines your knowledge from the past weeks. Throughout the 30 days, practice coding daily, consult Android documentation, and leverage online resources for additional guidance. Adapt the roadmap based on your progress and interests. Good luck with your Android app development journey! Free Resources: https://t.me/appsuser

🔥 𝐈𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭 𝐀𝐥𝐞𝐫𝐭 🔥 Many Of You Looking To Start Career In Data Analytics/Data Science  To Provide You FREE Career guidance ,We are conducting FREE Online MasterClasss😍 Join Our FREE Online Masterclass By Top Industry Experts  Roadmap To Become A Successful Data Scientist In Just 3 Months 𝐑𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐅𝐨𝐫 𝐅𝐑𝐄𝐄 👇:-  https://bit.ly/3CwTXyX (Limited Slots ..HurryUp🏃‍♂️ )  𝐃𝐚𝐭𝐞 & 𝐓𝐢𝐦𝐞:-  November 16, 2024, at 7 PM Dont miss this great opportunity 🤗

C++ Programming Roadmap | |-- Fundamentals | |-- Basics of Programming | | |-- Introduction to C++ | | |-- Setting Up Development Environment (IDE: Code::Blocks, Visual Studio, etc.) | | |-- Compiling and Running C++ Programs | | | |-- Syntax and Structure | | |-- Basic Syntax | | |-- Variables and Data Types | | |-- Operators (Arithmetic, Relational, Logical, Bitwise) | |-- Control Structures | |-- Conditional Statements | | |-- If-Else Statements | | |-- Switch Case | | | |-- Loops | | |-- For Loop | | |-- While Loop | | |-- Do-While Loop | | | |-- Jump Statements | | |-- Break, Continue | | |-- Goto Statement | |-- Functions and Scope | |-- Defining Functions | | |-- Function Syntax | | |-- Parameters and Arguments (Pass by Value, Pass by Reference) | | |-- Return Statement | | | |-- Function Overloading | | |-- Overloading Functions with Different Parameters | | | |-- Scope and Lifetime | | |-- Local and Global Scope | | |-- Static Variables | |-- Object-Oriented Programming (OOP) | |-- Basics of OOP | | |-- Classes and Objects | | |-- Member Functions and Data Members | | | |-- Constructors and Destructors | | |-- Constructor Types (Default, Parameterized, Copy) | | |-- Destructor Basics | | | |-- Inheritance | | |-- Single and Multiple Inheritance | | |-- Protected Access Specifier | | |-- Virtual Base Class | | | |-- Polymorphism | | |-- Function Overriding | | |-- Virtual Functions and Pure Virtual Functions | | |-- Abstract Classes | | | |-- Encapsulation and Abstraction | | |-- Access Specifiers (Public, Private, Protected) | | |-- Getters and Setters | | | |-- Operator Overloading | | |-- Overloading Operators (Arithmetic, Relational, etc.) | | |-- Friend Functions | |-- Advanced C++ | |-- Pointers and Dynamic Memory | | |-- Pointer Basics | | |-- Dynamic Memory Allocation (new, delete) | | |-- Pointer Arithmetic | | | |-- References | | |-- Reference Variables | | |-- Passing by Reference | | | |-- Templates | | |-- Function Templates | | |-- Class Templates | | | |-- Exception Handling | | |-- Try-Catch Blocks | | |-- Throwing Exceptions | | |-- Standard Exceptions | |-- Data Structures | |-- Arrays and Strings | | |-- One-Dimensional and Multi-Dimensional Arrays | | |-- String Handling | | | |-- Linked Lists | | |-- Singly and Doubly Linked Lists | | | |-- Stacks and Queues | | |-- Stack Operations (Push, Pop, Peek) | | |-- Queue Operations (Enqueue, Dequeue) | | | |-- Trees and Graphs | | |-- Binary Trees, Binary Search Trees | | |-- Graph Representation and Traversal (DFS, BFS) | |-- Standard Template Library (STL) | |-- Containers | | |-- Vectors, Lists, Deques | | |-- Stacks, Queues, Priority Queues | | |-- Sets, Maps, Unordered Maps | | | |-- Iterators | | |-- Input and Output Iterators | | |-- Forward, Bidirectional, and Random Access Iterators | | | |-- Algorithms | | |-- Sorting, Searching, and Manipulation | | |-- Numeric Algorithms | |-- File Handling | |-- Streams and File I/O | | |-- ifstream, ofstream, fstream | | |-- Reading and Writing Files | | |-- Binary File Handling | |-- Testing and Debugging | |-- Debugging Tools | | |-- gdb (GNU Debugger) | | |-- Valgrind for Memory Leak Detection | | | |-- Unit Testing | | |-- Google Test (gtest) | | |-- Writing and Running Tests | |-- Deployment and DevOps | |-- Version Control with Git | | |-- Integrating C++ Projects with GitHub | |-- Continuous Integration/Continuous Deployment (CI/CD) | | |-- Using Jenkins or GitHub | | |   |--Free courses | | |--imp.i115008.net/kjoq9V |   |   |--imp.i115008.net/5bmnKL |   |   |--Microsoft Documentation |   |   |--Udemy Course Join @free4unow_backup for more free resources ENJOY LEARNING 👍👍

Don't Miss This Great Opportunity 💥 𝐅𝐑𝐄𝐄 𝐎𝐧𝐥𝐢𝐧𝐞 𝐖𝐞𝐛𝐢𝐧𝐚𝐫 𝐎𝐧 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 😍 Roadmap To Start a Successful Analytics Career  Know The Upcoming trends shaping the future of business analytics. Eligibility :- Students ,Graduates & Working Professionals  𝐑𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐅𝐨𝐫 𝐅𝐑𝐄𝐄 👇:-  https://bit.ly/4fIjiEr (Limited Slots ..HurryUp🏃‍♂️ )  𝐃𝐚𝐭𝐞 & 𝐓𝐢𝐦𝐞:-  November 15, 2024, at 7 PM

30-days learning plan to master Data Structures and Algorithms (DSA) and prepare for coding interviews. ### Week 1: Foundations and Basic Data Structures Day 1-3: Arrays and Strings - Topics to Cover: - Array basics, operations (insertion, deletion, searching) - String manipulation - Two-pointer technique, sliding window technique - Practice Problems: - Two Sum - Maximum Subarray - Reverse a String - Longest Substring Without Repeating Characters Day 4-5: Linked Lists - Topics to Cover: - Singly linked list, doubly linked list, circular linked list - Common operations (insertion, deletion, reversal) - Practice Problems: - Reverse a Linked List - Merge Two Sorted Lists - Remove Nth Node From End of List Day 6-7: Stacks and Queues - Topics to Cover: - Stack operations (push, pop, top) - Queue operations (enqueue, dequeue) - Applications (expression evaluation, backtracking, breadth-first search) - Practice Problems: - Valid Parentheses - Implement Stack using Queues - Implement Queue using Stacks ### Week 2: Advanced Data Structures Day 8-10: Trees - Topics to Cover: - Binary Trees, Binary Search Trees (BST) - Tree traversal (preorder, inorder, postorder, level order) - Practice Problems: - Invert Binary Tree - Validate Binary Search Tree - Serialize and Deserialize Binary Tree Day 11-13: Heaps and Priority Queues - Topics to Cover: - Binary heap (min-heap, max-heap) - Heap operations (insert, delete, extract-min/max) - Applications (heap sort, priority queues) - Practice Problems: - Kth Largest Element in an Array - Top K Frequent Elements - Find Median from Data Stream Day 14: Hash Tables - Topics to Cover: - Hashing concept, hash functions, collision resolution (chaining, open addressing) - Applications (caching, counting frequencies) - Practice Problems: - Two Sum (using hash map) - Group Anagrams - Subarray Sum Equals K ### Week 3: Algorithms Day 15-17: Sorting and Searching Algorithms - Topics to Cover: - Sorting algorithms (quick sort, merge sort, bubble sort, insertion sort) - Searching algorithms (binary search, linear search) - Practice Problems: - Merge Intervals - Search in Rotated Sorted Array - Sort Colors - Find Peak Element Day 18-20: Recursion and Backtracking - Topics to Cover: - Basic recursion, tail recursion - Backtracking (N-Queens, Sudoku solver) - Practice Problems: - Permutations - Combination Sum - Subsets - Word Search Day 21: Divide and Conquer - Topics to Cover: - Basic concept, merge sort, quick sort, binary search - Practice Problems: - Median of Two Sorted Arrays - Pow(x, n) - Kth Largest Element in an Array (using divide and conquer) - Maximum Subarray (using divide and conquer) ### Week 4: Graphs and Dynamic Programming Day 22-24: Graphs - Topics to Cover: - Graph representations (adjacency list, adjacency matrix) - Traversal algorithms (DFS, BFS) - Shortest path algorithms (Dijkstra's, Bellman-Ford) - Practice Problems: - Number of Islands Day 25-27: Dynamic Programming - Topics to Cover: - Basic concept, memoization, tabulation - Common problems (knapsack, longest common subsequence) - Practice Problems: - Longest Increasing Subsequence - Maximum Product Subarray Day 28: Advanced Topics and Miscellaneous - Topics to Cover: - Bit manipulation - Greedy algorithms - Miscellaneous problems (trie, segment tree, disjoint set) - Practice Problems: - Single Number - Decode Ways - Minimum Spanning Tree ### Week 5: Review and Mock Interviews Day 29: Review and Weakness Analysis - Activities:   - Review topics you found difficult   - Revisit problems you struggled with Day 30: Mock Interviews and Practice - Activities:   - Conduct mock interviews with a friend or use online platforms   - Focus on communication and explaining your thought process Top DSA resources to crack coding interview 👉 GeekforGeeks 👉 Leetcode 👉 DSA Steps 👉 FreeCodeCamp 👉 Coding Interviews 👉 Best DSA Resources Join for more: https://t.me/free4unow_backup ENJOY LEARNING 👍👍

🚀 BITCOIN OVER 75.000$ ! In the last 3 days my subscribers have made over $20.000$ with my help ! We are now showing how to make money trading with Lisa for free in our channel! Our subscriber on average earns 3.000$ on full passive just by trading with Lisa. We have now opened free access to our VIP channel, only 100 people will get in for free, time is limited! JOIN THE CHANNEL AND TRADE WITH LISA https://t.me/+mo6goWxONzI4MThh https://t.me/+mo6goWxONzI4MThh https://t.me/+mo6goWxONzI4MThh

✅Meta interview questions : Most asked in last 30 days 1. 1249. Minimum Remove to Make Valid Parentheses 2. 408. Valid Word Abbreviation 3. 215. Kth Largest Element in an Array 4. 314. Binary Tree Vertical Order Traversal 5. 88. Merge Sorted Array 6. 339. Nested List Weight Sum 7. 680. Valid Palindrome II 8. 973. K Closest Points to Origin 9. 1650. Lowest Common Ancestor of a Binary Tree III 10. 1. Two Sum 11. 791. Custom Sort String 12. 56. Merge Intervals 13. 528. Random Pick with Weight 14. 1570. Dot Product of Two Sparse Vectors 15. 50. Pow(x, n) 16. 65. Valid Number 17. 227. Basic Calculator II 18. 560. Subarray Sum Equals K 19. 71. Simplify Path 20. 200. Number of Islands 21. 236. Lowest Common Ancestor of a Binary Tree 22. 347. Top K Frequent Elements 23. 498. Diagonal Traverse 24. 543. Diameter of Binary Tree 25. 1768. Merge Strings Alternately 26. 2. Add Two Numbers 27. 4. Median of Two Sorted Arrays 28. 7. Reverse Integer 29. 31. Next Permutation 30. 34. Find First and Last Position of Element in Sorted Array 31. 84. Largest Rectangle in Histogram 32. 146. LRU Cache 33. 162. Find Peak Element 34. 199. Binary Tree Right Side View 35. 938. Range Sum of BST 36. 17. Letter Combinations of a Phone Number 37. 125. Valid Palindrome 38. 153. Find Minimum in Rotated Sorted Array 39. 283. Move Zeroes 40. 523. Continuous Subarray Sum 41. 658. Find K Closest Elements 42. 670. Maximum Swap 43. 827. Making A Large Island 44. 987. Vertical Order Traversal of a Binary Tree 45. 1757. Recyclable and Low Fat Products 46. 1762. Buildings With an Ocean View 47. 2667. Create Hello World Function 48. 5. Longest Palindromic Substring 49. 15. 3Sum 50. 19. Remove Nth Node From End of List 51. 70. Climbing Stairs 52. 80. Remove Duplicates from Sorted Array II 53. 113. Path Sum II 54. 121. Best Time to Buy and Sell Stock 55. 127. Word Ladder 56. 128. Longest Consecutive Sequence 57. 133. Clone Graph 58. 138. Copy List with Random Pointer 59. 140. Word Break II 60. 142. Linked List Cycle II 61. 145. Binary Tree Postorder Traversal 62. 173. Binary Search Tree Iterator 63. 206. Reverse Linked List 64. 207. Course Schedule 65. 394. Decode String 66. 415. Add Strings 67. 437. Path Sum III 68. 468. Validate IP Address 70. 691. Stickers to Spell Word 71. 725. Split Linked List in Parts 72. 766. Toeplitz Matrix 73. 708. Insert into a Sorted Circular Linked List 74. 1091. Shortest Path in Binary Matrix 75. 1514. Path with Maximum Probability 76. 1609. Even Odd Tree 77. 1868. Product of Two Run-Length Encoded Arrays 78. 2022. Convert 1D Array Into 2D Array Top Coding Interview Resources to prepare for Microsoft, Amazon, Meta, Apple, Adobe, VMware, Visa, Twitter, LinkedIn, JP Morgan, Goldman Sachs, Oracle and Walmart 👇👇 https://topmate.io/coding/951517 All the best 👍👍

𝐅𝐑𝐄𝐄 𝐌𝐚𝐬𝐭𝐞𝐫𝐜𝐥𝐚𝐬𝐬 𝐎𝐧 𝐋𝐚𝐭𝐞𝐬𝐭 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬😍 - AI/ML - Data Analytics - Business Analytics - Data Science - Fullstack - UI/UX - Devops 🚀 3 Steps to Build Future-Proof Your IT Career! 𝐑𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐍𝐨𝐰 👇:- https://bit.ly/3YJPgJv (Limited Slots ..HurryUp🏃‍♂️ )  𝐃𝐚𝐭𝐞 & 𝐓𝐢𝐦𝐞:-  November 13, 2024, at 7 PM

Standing out in your career has never been harder. It’s also never been more important. 95.5% of employers believe that standing out is important for career advancement (Forbes). Here are 8 traits to help you stand out in your career: 1. Always Learning ↳ Keeps your skills sharp and shows you’re invested in growth. 2. Taking Initiative ↳ Demonstrates leadership potential and a proactive mindset. 3. Being Honest ↳ Builds trust with colleagues and superiors, setting you apart. 4. Staying Curious ↳ Drives new ideas and shows you’re always looking for solutions. 5. Being Dependable ↳ Establish you as a reliable person that others can count on. 6. Adapting to Change ↳ Shows resilience and the ability to thrive in dynamic environments. 7. Communicating Clearly ↳ Enhances collaboration and makes your ideas stand out. 8. Showing Empathy ↳ Builds strong connections and promotes a positive work culture. Visibility is not an advantage anymore. It’s a necessity. Master it, or risk blending in.

20 LeetCode Coding Patterns you should follow for coding interview preparation : 1. Sliding Window 2. Two Pointers 3. Binary Search 4. Fast and Slow Pointers 5. Merge Intervals 6. Top K Elements 7. K-way Merge 8. Breadth-First Search (BFS) 9. Depth-First Search (DFS) 10. Backtracking 11. Dynamic Programming (DP) 12. Kadane's Algorithm 13. Knapsack Problem 14. Tree Depth-First Search 15. Tree Breadth-First Search 16. Topological Sort 17. Trie 18. Graph - Bipartite Check 19. Bitwise XOR 20. Sliding Window - Optimal Mastering these patterns will give you a solid foundation to tackle a wide variety of coding problems, ranging from arrays and strings to graphs and trees. By internalizing these patterns, you'll become more efficient at solving LeetCode problems and increase your chances of acing coding interviews. Best DSA Resources: 👇 https://topmate.io/coding/886874 All the best 👍👍