Coding Interview Resources

✅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 👍👍

⌨️ JavaScript: 5 Useful Web APIs

120 Days DSA Roadmap: DAYS 1-5 : 1. Language basics 2. Space & Time Complexity DAYS 6-15 : 1. Pattern Printing 2. Recursion 3. Backtracking DAYS 16-30 : Basic data structures 1. Arrays 2. Linked List 3. Stacks & Queues DAYS 31-40 : Algorithms 1. Searching 2. Sorting - Bubble sort, Insertion sort, Selection sort, Merge sort, Quick sort ✅ Suggestion to start with online contests and hackathons DAYS 41-60: Complex data structures 1. Hashmaps 2. Nodes 3. Trees 4. Heaps 5. Sliding window (technique) DAYS 61-85: Graphs 1. BFS 2. DFS 3. Dijkstra 4. Floyd Warshall 5. Prim 6. Kruskal 7. Kosaraju’s algorithm 8. Topological Sort 9. Bellman Ford 10. Normal DSU 11. DSU by rank DAYS 86-95: Dynamic Programming 1. Memoisation 2. Tabulation DAYS 96-105: 1. Concepts of OOPs DAYS 106-120: 1. Number Theory 2. Bit Manipulation 3. Tries Best DSA RESOURCES: https://topmate.io/coding/886874 All the best 👍👍

Today, I got a new website which share amazing jobs & internship opportunities Step 1:- 👇Upload Your Resume  https://bit.ly/Jobinternshipfree Step 2:- Fill in your professional details like education & work experience (if any) Step 3 :- Select your skills & preferred job role(e.g., data analyst, business analyst, data scientist, etc.) & location  Apply for the jobs & internship opportunities that matches with your profile.

API design involves making decisions about how your API will interact with consumers. The major API design choices are: REST (Representational State Transfer): It uses HTTP methods (GET, POST, PUT, DELETE) for CRUD operations on resources. It's stateless and commonly used for web-based APIs GraphQL: Query language for APIs, it allows clients to request specific data RPC (Remote Procedure Call): High-performance, language-agnostic framework, often used in microservices architectures

🔟 𝘁𝗶𝗽𝘀 𝗳𝗼𝗿 𝗻𝗲𝘄 𝗰𝗼𝗱𝗲𝗿𝘀: 🔖 1. Learn Fundamentals:  Use W3Schools, FreeCodeCamp, or MDN for solid basics. 2. Watch and Code Along:  Follow YouTube tutorials to code in real-time. 3. Practice Regularly:  Build small projects to sharpen your skills. 4. Join Coding Communities:  Engage on platforms like X, Discord, and Reddit for support. 5. Use AI Tools Wisely: Leverage tools like ChatGPT responsibly to aid learning. 6. Master Git and Version Control:  Learn to manage your code effectively. 7. Stay Updated:  Follow tech blogs, newsletters, and podcasts. 8. Network:  Attend meetups, hackathons, and online coding events. 9. Explore Open Source:  Contribute to projects to gain experience. 10.Never Stop Learning:  Technology evolves—keep exploring new languages and frameworks. Best Programming Resources: https://topmate.io/coding/886839 All the best 👍👍

PREPARING FOR AN ONLINE INTERVIEW? 10 basic tips to consider when invited/preparing for an online interview: 1. Get to know the online technology that the interviewer(s) will use. Is it a phone call, WhatsApp, Skype or Zoom interview? If not clear, ask. 2. Familiarize yourself with the online tools that you’ll be using. Understand how Zoom/Skype works and test it well in advance. Test the sound and video quality. 3. Ensure that your internet connection is stable. If using mobile data, make sure it’s adequate to sustain the call to the end. 4. Ensure the lighting and the background is good. Remove background clutter. Isolate yourself in a place where you’ll not have any noise distractions. 5. For Zoom/Skype calls, use your desktop or laptop instead of your phone. They’re more stable especially for video calls. 6. Mute all notifications on your computer/phone to avoid unnecessary distractions. 7. Ensure that your posture is right. Just because it’s a remote interview does not mean you slouch on your couch. Maintain an upright posture. 8. Prepare on the other job specifics just like you would for a face-to-face interview 9. Dress up like you would for a face-to-face interview. 10. Be all set at least 10 minutes to the start of interview.

Best suited IDE's for programming languages: 1. JavaScript => VSCode 2. Python => PyCharm 3. C# => Visual Studio 4. Java => IntelliJ IDEA 5. Ruby => Ruby Mine 6. C & C++ => CLion

https://topmate.io/coding/886874 If you're a job seeker, these well structured document DSA resources will help you to know and learn all the real time DSA & OOPS Interview questions with their exact answer. folks who are having 0-4+ years of experience have cracked the interview using this guide! Please use the above link to avail them!👆 NOTE: -Most people hoard resources without actually opening them even once! The reason for keeping a small price for these resources is to ensure that you value the content available inside this and encourage you to make the best out of it. Hope this helps in your job search journey... All the best!👍✌️

⭕ WIPRO INTERVIEW EXPERIENCE ⭕ 1) Intro. 2) Willing to Relocate. 3) Service Agreement. 4) about Internship (if you have done)    (details like what did you do there or    learnt there, how many other people    you worked with). 5) About Project ( details like name,      what made you do that project, what      Tech Stacks used, Difficulties faced,      whats the use of that project ). 6) In which Programming language you     are proficient (i said python ). 7) Why python and why not any other     languages. 8) Any one simple Theoritical question     from that language you mentioned    (asked limitations of python). Best DSA RESOURCES: https://topmate.io/coding/886874 All the best 👍👍

𝗦𝘁𝗲𝗽𝘀 𝗧𝗼 𝗣𝗿𝗲𝗽𝗮𝗿𝗲 𝗙𝗼𝗿 𝗮 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 👉 𝗞𝗻𝗼𝘄 𝘁𝗵𝗲 𝗝𝗼𝗯: Review the job description. 👉 𝗕𝗮𝘀𝗶𝗰𝘀: Revise fundamental concepts. 👉 𝗖𝗼𝗱𝗲 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲: Solve coding problems. 👉 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀: Be ready to discuss past work. 👉 𝗠𝗼𝗰𝗸 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝘀: Practice with friends or online. 👉 𝗦𝘆𝘀𝘁𝗲𝗺 𝗗𝗲𝘀𝗶𝗴𝗻: Review basics if needed. 👉 𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀: Prepare some for the interviewer. 👉 𝗥𝗲𝘀𝘁: Sleep well and stay calm. Remember, practice and confidence are the key! Good luck with your technical interview! 🌟👍 You can check these resources for Coding interview Preparation All the best 👍👍

🏟 Here is a complete roadmap to learn Data Structures and Algorithms (DSA) 🏟 1. Basics of Programming: Start by learning the basics of a programming language like Python, Java, or C++. Understand concepts like variables, loops, functions, and arrays. 2. Data Structures: Study fundamental data structures like arrays, linked lists, stacks, queues, trees, graphs, and hash tables. Understand the operations that can be performed on these data structures and their time complexities. 3. Algorithms: Learn common algorithms like searching, sorting, recursion, dynamic programming, greedy algorithms, and divide and conquer. Understand how these algorithms work and their time complexities. 4. Problem Solving: Practice solving coding problems on platforms like LeetCode, HackerRank, or Codeforces. Start with easy problems and gradually move to medium and hard problems. 5. Complexity Analysis: Learn how to analyze the time and space complexity of algorithms. Understand Big O notation and how to calculate the complexity of different algorithms. 6. Advanced Data Structures: Study advanced data structures like AVL trees, B-trees, tries, segment trees, and fenwick trees. Understand when and how to use these data structures in problem-solving. 7. Graph Algorithms: Learn graph traversal algorithms like BFS and DFS. Study algorithms like Dijkstra's algorithm, Bellman-Ford algorithm, and Floyd-Warshall algorithm for shortest path problems. 8. Dynamic Programming: Master dynamic programming techniques for solving complex problems efficiently. Practice solving dynamic programming problems to build your skills. 9. Practice and Review: Regularly practice coding problems and review your solutions. Analyze your mistakes and learn from them to improve your problem-solving skills. 10. Mock Interviews: Prepare for technical interviews by participating in mock interviews and solving interview-style coding problems. Practice explaining your thought process and reasoning behind your solutions. Best DSA RESOURCES: https://topmate.io/coding/886874 All the best 👍👍

Here's a concise cheat sheet to help you get started with Python for Data Analytics. This guide covers essential libraries and functions that you'll frequently use. 1. Python Basics - Variables: x = 10 y = "Hello" - Data Types:   - Integers: x = 10   - Floats: y = 3.14   - Strings: name = "Alice"   - Lists: my_list = [1, 2, 3]   - Dictionaries: my_dict = {"key": "value"}   - Tuples: my_tuple = (1, 2, 3) - Control Structures:   - if, elif, else statements   - Loops:    

    for i in range(5):
        print(i)
    

  - While loop:   

    while x < 5:
        print(x)
        x += 1
    

2. Importing Libraries - NumPy:

  import numpy as np
  

- Pandas:

  import pandas as pd
  

- Matplotlib:

  import matplotlib.pyplot as plt
  

- Seaborn:

  import seaborn as sns
  

3. NumPy for Numerical Data - Creating Arrays:

  arr = np.array([1, 2, 3, 4])
  

- Array Operations:

  arr.sum()
  arr.mean()
  

- Reshaping Arrays:

  arr.reshape((2, 2))
  

- Indexing and Slicing:

  arr[0:2]  # First two elements
  

4. Pandas for Data Manipulation - Creating DataFrames:

  df = pd.DataFrame({
      'col1': [1, 2, 3],
      'col2': ['A', 'B', 'C']
  })
  

- Reading Data:

  df = pd.read_csv('file.csv')
  

- Basic Operations:

  df.head()          # First 5 rows
  df.describe()      # Summary statistics
  df.info()          # DataFrame info
  

- Selecting Columns:

  df['col1']
  df[['col1', 'col2']]
  

- Filtering Data:

  df[df['col1'] > 2]
  

- Handling Missing Data:

  df.dropna()        # Drop missing values
  df.fillna(0)       # Replace missing values
  

- GroupBy:

  df.groupby('col2').mean()
  

5. Data Visualization - Matplotlib:

  plt.plot(df['col1'], df['col2'])
  plt.xlabel('X-axis')
  plt.ylabel('Y-axis')
  plt.title('Title')
  plt.show()
  

- Seaborn:

  sns.histplot(df['col1'])
  sns.boxplot(x='col1', y='col2', data=df)
  

6. Common Data Operations - Merging DataFrames:

  pd.merge(df1, df2, on='key')
  

- Pivot Table:

  df.pivot_table(index='col1', columns='col2', values='col3')
  

- Applying Functions:

  df['col1'].apply(lambda x: x*2)
  

7. Basic Statistics - Descriptive Stats:

  df['col1'].mean()
  df['col1'].median()
  df['col1'].std()
  

- Correlation:

  df.corr()
  

This cheat sheet should give you a solid foundation in Python for data analytics. As you get more comfortable, you can delve deeper into each library's documentation for more advanced features. I have curated the best interview resources to crack Python Interviews 👇👇 https://topmate.io/analyst/907371 Hope you'll like it Like this post if you need more resources like this 👍❤️

When you’re in an interview, it’s super important to know how to talk about your projects in a way that impresses the interviewer. Here are some key points to help you do just that: ➤ 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗢𝘃𝗲𝗿𝘃𝗶𝗲𝘄: - Start with a quick summary of the project you worked on. What was it all about? What were the main goals? Keep it short and sweet something you can explain in about 30 seconds. ➤ 𝗣𝗿𝗼𝗯𝗹𝗲𝗺 𝗦𝘁𝗮𝘁𝗲𝗺𝗲𝗻𝘁: - What problem were you trying to solve with this project? Explain why this problem was important and needed addressing. ➤ 𝗣𝗿𝗼𝗽𝗼𝘀𝗲𝗱 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻: - Describe the solution you came up with. How does it work, and why is it a good fix for the problem? ➤ 𝗬𝗼𝘂𝗿 𝗥𝗼𝗹𝗲: - Talk about what you specifically did. What were your main tasks? Did you face any challenges, and how did you overcome them? Make sure it’s clear whether you were leading the project, a key player, or supporting the team. ➤ 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝗶𝗲𝘀 𝗮𝗻𝗱 𝗧𝗼𝗼𝗹𝘀: - Mention the tech and tools you used. This shows your technical know-how and your ability to choose the right tools for the job. ➤ 𝗜𝗺𝗽𝗮𝗰𝘁 𝗮𝗻𝗱 𝗔𝗰𝗵𝗶𝗲𝘃𝗲𝗺𝗲𝗻𝘁𝘀: - Share the results of your project. Did it make things better? How? Mention any improvements, efficiencies, or positive feedback you got. ➤ 𝗧𝗲𝗮𝗺 𝗖𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝗼𝗻: - Talk about how you collaborated. What was your role in the team? How did you communicate and contribute to the team’s success? ➤ 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗮𝗻𝗱 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁: - Reflect on what you learned from the project. What new skills did you gain, and what would you do differently next time? ➤ 𝗧𝗶𝗽𝘀 𝗳𝗼𝗿 𝗬𝗼𝘂𝗿 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗣𝗿𝗲𝗽𝗮𝗿𝗮𝘁𝗶𝗼𝗻: - Be ready with a 30 second elevator pitch about your projects, and also have a five-minute detailed overview ready. - If there’s a pause after you describe the project, don’t hesitate to ask if they’d like more details or if there’s a specific part they’re interested in. By preparing your project details thoroughly and understanding what the interviewer is looking for, you can talk about your experience in a way that really showcases your skills and increases your chances of getting the job. Best DSA RESOURCES: https://topmate.io/coding/886874 All the best 👍👍

Is DSA important for interviews? Yes, DSA (Data Structures and Algorithms) is very important for interviews, especially for software engineering roles. I often get asked, What do I need to start learning DSA? Here's the roadmap for getting started with Data Structures and Algorithms (DSA): 𝗣𝗵𝗮𝘀𝗲 𝟭: 𝗙𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀 1. Introduction to DSA - Understand what DSA is and why it's important. - Overview of complexity analysis (Big O notation). 2. Complexity Analysis - Time Complexity - Space Complexity 3. Basic Data Structures - Arrays - Linked Lists - Stacks - Queues 4. Basic Algorithms - Sorting (Bubble Sort, Selection Sort, Insertion Sort) - Searching (Linear Search, Binary Search) 5. OOP (Object-Oriented Programming) 𝗣𝗵𝗮𝘀𝗲 𝟮: 𝗜𝗻𝘁𝗲𝗿𝗺𝗲𝗱𝗶𝗮𝘁𝗲 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀 1. Two Pointers Technique - Introduction and basic usage - Problems: Pair Sum, Triplets, Sorted Array Intersection etc.. 2. Sliding Window Technique - Introduction and basic usage - Problems: Maximum Sum Subarray, Longest Substring with K Distinct Characters, Minimum Window Substring etc.. 3. Line Sweep Algorithms - Introduction and basic usage - Problems: Meeting Rooms II, Skyline Problem 4. Recursion 5. Backtracking 6. Sorting Algorithms - Merge Sort - Quick Sort 7. Data Structures - Hash Tables - Trees (Binary Trees, Binary Search Trees) - Heaps 𝗣𝗵𝗮𝘀𝗲 𝟯: 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀 1. Graph Algorithms - Graph Representation (Adjacency List, Adjacency Matrix) - BFS (Breadth-First Search) - DFS (Depth-First Search) - Shortest Path Algorithms (Dijkstra's, Bellman-Ford) - Minimum Spanning Tree (Kruskal's, Prim's) 2. Dynamic Programming - Basic Problems (Fibonacci, Knapsack etc..) - Advanced Problems (Longest Increasing Subsea mice, Matrix Chain Subsequence, Multiplication etc..) 3. Advanced Trees - AVL Trees - Red-Black Trees - Segment Trees - Trie 𝗣𝗵𝗮𝘀𝗲 𝟰: 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲 𝗮𝗻𝗱 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 1. Competitive Programming Platforms: LeetCode, Codeforces, HackerRank, CodeChef Solve problems daily 2. Mock Interviews - Participate in mock interviews to simulate real interview scenarios. - DSA interviews assess your ability to break down complex problems into smaller steps. Best DSA RESOURCES: https://topmate.io/coding/886874 All the best 👍👍

Beginner’s Roadmap to Learn Data Structures & Algorithms 1. Foundations: Start with the basics of programming and mathematical concepts to build a strong foundation. 2. Data Structure: Dive into essential data structures like arrays, linked lists, stacks, and queues to organise and store data efficiently. 3. Searching & Sorting: Learn various search and sort techniques to optimise data retrieval and organisation. 4. Trees & Graphs: Understand the concepts of binary trees and graph representation to tackle complex hierarchical data. 5. Recursion: Grasp the principles of recursion and how to implement recursive algorithms for problem-solving. 6. Advanced Data Structures: Explore advanced structures like hashing, heaps, and hash maps to enhance data manipulation. 7. Algorithms: Master algorithms such as greedy, divide and conquer, and dynamic programming to solve intricate problems. 8. Advanced Topics: Delve into backtracking, string algorithms, and bit manipulation for a deeper understanding. 9. Problem Solving: Practice on coding platforms like LeetCode to sharpen your skills and solve real-world algorithmic challenges. 10. Projects & Portfolio: Build real-world projects and showcase your skills on GitHub to create an impressive portfolio. Best DSA RESOURCES: https://topmate.io/coding/886874 All the best 👍👍

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3 preparation mistakes that keeps you jobless 👉Waiting for the right time to apply 👉Not stepping up while solving problem 👉Deciding Dev or DSA Try these 3 tips to increase your chances of getting hired: 1.There is never a right time to apply, as soon as you feel a bit confident in preparation go for it. 2.Solving same level of questions every day won't help you build logical thinking. Instead keep stepping up towards good level of questions. 3.Don't fall into the trap of Dev Vs DSA. Everything is important. It's just varies from company to company when it's come to what is more likely to be asked. Best DSA RESOURCES: https://topmate.io/coding/886874 keep learning , keep growing

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