Mastering LinkedLists: Key Questions You Should Know

Easy:
📌 Reverse Linked List: https://lnkd.in/g7qP9-YU
📌 Merge Two Sorted Lists: https://lnkd.in/gRfC6yyF
📌 Remove Nth Node From End of List: https://lnkd.in/gGnGF75X
📌 Delete Node in a Linked List: https://lnkd.in/gqzDgFpN
📌 Palindrome Linked List: https://lnkd.in/gmEjY4gr

Medium:
📌 Add Two Numbers: https://lnkd.in/gvDxHySa
📌 Swap Nodes in Pairs: https://lnkd.in/gnhqwidB
📌 Odd Even Linked List: https://lnkd.in/gS2QpJAw
📌 Intersection of Two Linked Lists: https://lnkd.in/gpwnpK8M
📌 Rotate List: https://lnkd.in/gKg_3D34

Hard:
📌 Merge k Sorted Lists: https://lnkd.in/g7wK8H8v
📌 Reverse Nodes in k-Group: https://lnkd.in/gUNaexhD
📌 Copy List with Random Pointer: https://lnkd.in/gBWcFRKe
📌 LRU Cache: https://lnkd.in/gURyUMZK
📌 Flatten a Multilevel Doubly Linked List: https://lnkd.in/gCtgKNwn

By understanding the answers to these questions, you can build a solid foundation for solving LinkedList-related problems and tackling algorithmic challenges!

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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

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ENJOY LEARNING 👍👍

DSA question by understanding patterns

If the input array is sorted then
- Binary search
- Two pointers

If asked for all permutations/subsets then
- Backtracking

If given a tree then
- DFS
- BFS

If given a graph then
- DFS
- BFS

If given a linked list then
- Two pointers

If recursion is banned then
- Stack

If must solve in-place then
- Swap corresponding values
- Store one or more different values in the same pointer

If asked for maximum/minimum subarray/ subset/options then
- Dynamic programming

If asked for top/least K items then
- Heap
- QuickSelect

If asked for common strings then
- Map
- Trie

Else
- Map/Set for O(1) time & O(n) space
- Sort input for O(nlogn) time and O(1) space

𝐉𝐨𝐢𝐧 𝐭𝐡𝐢𝐬 𝐭𝐞𝐥𝐞𝐠𝐫𝐚𝐦 𝐠𝐫𝐨𝐮𝐩 𝐟𝐨𝐫 𝐩𝐫𝐞𝐦𝐢𝐮𝐦 𝐉𝐨𝐛𝐬/Notes: https://t.me/getjobss

Step-by-Step Approach

➊ Learn One Programming Language
↓
➋ Fundamentals → Time & Space Complexity
↓
➌ Brute Force Algorithms
↓
➍ Basic Data Structures → Array, Linked List
↓
➎ Simple Search Algorithm
↓
➏ Sorting Techniques → Bubble, Selection, Insertion
↓
➐ Slightly Complex Algorithms → Recursion, DnC
↓
➑ Complex Data Structures → Stack, Queue, Tree

DSA Interview Preparation Resources: https://topmate.io/coding/886874

ENJOY LEARNING 👍👍

Steps to learn Data Structures and Algorithms (DSA) with Python

1. Learn Python: If you're not already familiar with Python, start by learning the basics of the language. There are many online resources and tutorials available for free.

2. Understand the Basics: Before diving into DSA, make sure you have a good grasp of Python's syntax, data types, and basic programming concepts. Use free resources from @dsabooks to help you in learning journey.

3. Pick Good Learning Resources: Choose a good book, online course, or tutorial series on DSA with Python. Most of the free stuff is already posted on the channel @crackingthecodinginterview

4. Data Structures: Begin with fundamental data structures like lists, arrays, stacks, queues, linked lists, trees, graphs, and hash tables. Understand their properties, operations, and when to use them.

5. Algorithms: Study common algorithms such as searching (binary search, linear search), sorting (quick sort, merge sort), and dynamic programming. Learn about their time and space complexity.

6. Practice: The key to mastering DSA is practice. Solve a wide variety of problems to apply your knowledge. Websites like LeetCode and HackerRank provide a vast collection of problems.

7. Analyze Complexity: Learn how to analyze the time and space complexity of algorithms. Big O notation is a crucial concept in DSA.

8. Implement Algorithms: Implement algorithms and data structures from scratch in Python. This hands-on experience will deepen your understanding.

9. Project Work: Apply DSA to real projects. This could be building a simple game, a small web app, or any software that requires efficient data handling. Check channel @programming_experts if you need project ideas.

10. Seek Help and Collaborate: Don't hesitate to ask for help when you're stuck. Engage in coding communities, forums, or collaborate with others to gain new insights.

11. Review and Revise: Periodically review what you've learned. Reinforce your understanding by revisiting data structures and algorithms you've studied.

12. Competitive Programming: Participate in competitive programming contests. They are a great way to test your skills and improve your problem-solving abilities.

13. Stay Updated: DSA is an ever-evolving field. Stay updated with the latest trends and algorithms.

14. Contribute to Open Source: Consider contributing to open source projects. It's a great way to apply your knowledge and work on real-world code.

15. Teach Others: Teaching what you've learned to others can deepen your understanding. You can create tutorials or mentor someone.

Join @free4unow_backup for more free courses

ENJOY LEARNING 👍👍

VS Code Shortcuts

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.

✅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

DSA Interview Preparation Resources: https://topmate.io/coding/886874

ENJOY LEARNING 👍👍

Tech Interviews

ChatGPT can help you land your dream job twice as fast. Here are 8 powerful ChatGPT prompts will 10X your interview chances.

Free book to master ChatGPT: https://t.me/InterviewBooks/166

1. Customizing Your Resume ChatGPT prompt: "Can you make changes to my resume to fit the [Job Title] role at [Company]? Here's the job description: [Paste Job Description], and resume: [Paste Resume]."

2. Creating a Professional Summary ChatGPT prompt: "Using my resume, can you create a professional summary for me aligned to this [Job Title]." [Paste Resume]

3. Understanding Job Descriptions ChatGPT prompt: "What are the main responsibilities for this job? Please list the top three responsibilities required for [Job Title]." [Paste Job Description]

4. Improving Your Resume Bullets ChatGPT prompt: "Please rewrite this bullet point from my resume using clear and impactful language while highlighting my accomplishments. [Paste Resume]"

5. Writing a LinkedIn Summary ChatGPT prompt: "Can you write a summary for my LinkedIn profile using my resume [Paste Resume]?"

6. Job Applications with ChatGPT ChatGPT prompt: "Can you identify my [Skills] experience from my resume [Paste Resume]? Please describe my specific [Skills] experience in conversational, clear language as if you were me."

7. Crafting Your Cover Letter ChatGPT prompt: "Can you write a personalized cover letter for the [Job Title] position at [Company]? Here's the job description: [Paste Job Description], and my current resume: [Paste Resume]."

8. Preparing for Interviews ChatGPT prompt: "What skills and experiences should I emphasize during an interview for the [Job Title] role in [Specific Industry]?"

ENJOY LEARNING 👍👍

Shoutout to all the late-night coders—may your coffee be strong and your bugs be few!

How to start learning Generative AI

Best way to prepare for Python interviews 👇👇

1. Fundamentals: Strengthen your understanding of Python basics, including data types, control structures, functions, and object-oriented programming concepts.

2. Data Structures and Algorithms: Familiarize yourself with common data structures (lists, dictionaries, sets, etc.) and algorithms. Practice solving coding problems on platforms like LeetCode or HackerRank.

3. Problem Solving: Develop problem-solving skills by working on real-world scenarios. Understand how to approach and solve problems efficiently using Python.

4. Libraries and Frameworks: Be well-versed in popular Python libraries and frameworks relevant to the job, such as NumPy, Pandas, Flask, or Django. Demonstrate your ability to apply these tools in practical situations.

5. Web Development (if applicable): If the position involves web development, understand web frameworks like Flask or Django. Be ready to discuss your experience in building web applications using Python.

6. Database Knowledge: Have a solid understanding of working with databases in Python. Know how to interact with databases using SQLAlchemy or Django ORM.

7. Testing and Debugging: Showcase your proficiency in writing unit tests and debugging code. Understand testing frameworks like pytest and debugging tools available in Python.

8. Version Control: Familiarize yourself with version control systems, particularly Git, and demonstrate your ability to collaborate on projects using Git.

9. Projects: Showcase relevant projects in your portfolio. Discuss the challenges you faced, solutions you implemented, and the impact of your work.

10. Soft Skills: Highlight your communication and collaboration skills. Be ready to explain your thought process and decision-making during technical discussions.

Best Resource to learn Python

Python Interview Questions with Answers

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Python for Data Analysis and Visualization

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New developers: Whenever you work on something interesting, write it down in a document which you keep updating. This will be very helpful when you need to create a resume or have to talk about your achievements in an interview. (Or for college essays.)

I can guarantee you that if you don't do this, you will forget half the interesting things you've done; and for a majority of us, our brains are experts in convincing us that we haven't really done anything interesting.

Top 21 skills to learn this year 👇

1. Artificial Intelligence and Machine Learning: Understanding AI algorithms and applications.
2. Data Science: Proficiency in tools like Python/ R, Jupyter Notebook, and GitHub, with the ability to apply data science algorithms to solve real-world problems.
3. Cybersecurity: Protecting data and systems from cyber threats.
4. Cloud Computing: Proficiency in platforms like AWS, Azure, and Google Cloud.
5. Blockchain Technology: Understanding blockchain architecture and applications beyond cryptocurrencies.
6. Digital Marketing: Expertise in SEO, social media, and online advertising.
7. Programming: Skills in languages such as Python, JavaScript, and Go.
8. UX/UI Design: Creating intuitive and effective user interfaces and experiences.
9. Consulting: Expertise in providing strategic advice, improving business processes, and implementing solutions to drive business growth.
10. Data Analysis and Visualization: Proficiency in tools like Excel, SQL, Tableau, and Power BI to analyze and present data effectively.
11. Business Analysis & Project Management: Using tools and methodologies like Agile and Scrum.
12. Remote Work Tools: Proficiency in tools for remote collaboration and productivity.
13. Financial Literacy: Understanding personal finance, investment, and cryptocurrencies.
14. Emotional Intelligence: Skills in empathy, communication, and relationship management.
15. Business Acumen: A deep understanding of how businesses operate, including strategic thinking, market analysis, and financial literacy.
16. Investment Banking: Knowledge of financial markets, valuation methods, mergers and acquisitions, and financial modeling.
17. Mobile App Development: Skills in developing apps for iOS and Android using Swift, Kotlin, or React Native.
18. Financial Management: Proficiency in financial planning, analysis, and tools like QuickBooks and SAP.
19. Web Development: Proficiency in front-end and back-end development using HTML, CSS, JavaScript, and frameworks like React, Angular, and Node.js.
20. Data Engineering: Skills in designing, building, and maintaining data pipelines and architectures using tools like Hadoop, Spark, and Kafka.
21. Soft Skills: Improving leadership, teamwork, and adaptability skills.

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Here are some of the most popular python project ideas: 💡

Simple Calculator
Text-Based Adventure Game
Number Guessing Game
Password Generator
Dice Rolling Simulator
Mad Libs Generator
Currency Converter
Leap Year Checker
Word Counter
Quiz Program
Email Slicer
Rock-Paper-Scissors Game
Web Scraper (Simple)
Text Analyzer
Interest Calculator
Unit Converter
Simple Drawing Program
File Organizer
BMI Calculator
Tic-Tac-Toe Game
To-Do List Application
Inspirational Quote Generator
Task Automation Script
Simple Weather App
Automate data cleaning and analysis (EDA)
Sales analysis
Sentiment analysis
Price prediction
Customer Segmentation
Time series forecasting
Image classification
Spam email detection
Credit card fraud detection
Market basket analysis
NLP, etc

These are just starting points. Feel free to explore, combine ideas, and personalize your projects based on your interest and skills. 🎯

Here's a 30-day roadmap to learn C++ up to an intermediate level, along with project ideas:

Week 1: C++ Basics
*Day 1-2:*
- Day 1: Install a C++ compiler (e.g., Visual Studio, Code::Blocks, or g++) and write your first "Hello, World!" program.
- Day 2: Understand C++ syntax, data types, and variables.

*Day 3-4:*
- Day 3: Learn about basic input and output operations in C++ using cin and cout.
- Day 4: Study operators and perform arithmetic and logical operations.

*Day 5-7:*
- Day 5: Explore control flow with if-else statements and loops (for, while, do-while).
- Day 6: Understand switch statements and how to use them for menu-driven programs.
- Day 7: Practice writing small programs involving conditions and loops.

Week 2: Functions and Object-Oriented Programming
*Day 8-9:*
- Day 8: Learn about functions (methods) in C++ and how to define your own functions.
- Day 9: Study function parameters, return types, and function overloading.

*Day 10-12:*
- Day 10: Understand the basics of object-oriented programming (OOP) in C++, including classes and objects.
- Day 11: Dive into constructors, destructors, and operator overloading.
- Day 12: Explore encapsulation, inheritance, and polymorphism.

*Day 13-14:*
- Day 13: Study C++ namespaces and access specifiers (public, private, protected).
- Day 14: Practice creating classes and objects for real-world applications.

Week 3: Data Structures and Standard Template Library (STL)
*Day 15-17:*
- Day 15: Dive into C++ arrays and understand their usage.
- Day 16: Explore the Standard Template Library (STL) and containers like vectors and lists.
- Day 17: Learn about iterating through containers using iterators.

*Day 18-19:*
- Day 18: Study other STL components like maps, sets, and queues.
- Day 19: Understand when and how to use different STL containers in C++.

*Day 20-21:*
- Day 20: Explore exception handling in C++ and how to handle runtime errors.
- Day 21: Practice working with try-catch blocks and handling exceptions effectively.

Week 4: Intermediate Topics and Projects
*Day 22-23:*
- Day 22: Learn about file handling in C++, including reading and writing files.
- Day 23: Create a small project that involves file operations, like a text-based note-taking application.

*Day 24-26:*
- Day 24: Study C++ pointers, references, and dynamic memory allocation.
- Day 25: Explore more advanced C++ topics like multithreading or creating a simple game using libraries like SDL or SFML.
- Day 26: Work on a project that involves pointers, references, or multithreading.

*Day 27-28:*
- Day 27: Explore more advanced C++ libraries and frameworks that interest you (e.g., Boost or Qt).
- Day 28: Work on a more complex project that combines your knowledge from the past weeks. For example, create a small database application using SQLite and C++.

*Day 29-30:*
- Day 29: Review and revisit any topics you found challenging.
- Day 30: Continue building projects and exploring areas of C++ that interest you.

Remember to practice coding daily, and don't hesitate to explore additional resources, online tutorials, and forums to enhance your C++ skills. Good luck with your C++ learning journey!

ENJOY LEARNING 👍👍