Don't overwhelm to learn Git,🙌

Git is only this much👇😇

1.Core:
• git init
• git clone
• git add
• git commit
• git status
• git diff
• git checkout
• git reset
• git log
• git show
• git tag
• git push
• git pull

2.Branching:
• git branch
• git checkout -b
• git merge
• git rebase
• git branch --set-upstream-to
• git branch --unset-upstream
• git cherry-pick

3.Merging:
• git merge
• git rebase

4.Stashing:
• git stash
• git stash pop
• git stash list
• git stash apply
• git stash drop

5.Remotes:
• git remote
• git remote add
• git remote remove
• git fetch
• git pull
• git push
• git clone --mirror

6.Configuration:
• git config
• git global config
• git reset config

7. Plumbing:
• git cat-file
• git checkout-index
• git commit-tree
• git diff-tree
• git for-each-ref
• git hash-object
• git ls-files
• git ls-remote
• git merge-tree
• git read-tree
• git rev-parse
• git show-branch
• git show-ref
• git symbolic-ref
• git tag --list
• git update-ref

8.Porcelain:
• git blame
• git bisect
• git checkout
• git commit
• git diff
• git fetch
• git grep
• git log
• git merge
• git push
• git rebase
• git reset
• git show
• git tag

9.Alias:
• git config --global alias.<alias> <command>

10.Hook:
• git config --local core.hooksPath <path>

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✅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 👍👍

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 👍👍

Guys, Big Announcement!

We’ve officially crossed 4 Lakh followers on this journey together — and it’s time to step up now! ❤️

I’m launching a Coding Interview Prep Series — designed for everyone from beginners to those polishing their skills for FAANG-level interviews.

This will be a structured, step-by-step journey — with short explanations, real coding examples, and mini-challenges after every topic to build real muscle memory.

Here’s what’s coming in the next few weeks:

Week 1: The Very Basics

- What is an Algorithm?

- What is Data Structure?

- Understanding Time Complexity (Big O Notation - made simple!)

- Basic Math for Coding Interviews

- Problem Solving Approach (How to break down a question)


Week 2: Arrays & Strings — Your Building Blocks

- Introduction to Arrays and Strings

- Common Operations (Insert, Delete, Search)

- Two Pointer Techniques (Easy to Medium problems)

- Sliding Window Problems (Optimization techniques)

- String Manipulation Tricks for Interviews


Week 3: Hashing & Recursion

- HashMaps and HashSets (Power tools for coders!)

- Solving Problems using Hashing

- Introduction to Recursion

- Base Case and Recursive Case (Explained like a 5-year-old)

- Classic Recursion Problems


Week 4: Linked Lists, Stacks & Queues

- Singly vs Doubly Linked List

- Stack Operations and Problems (Valid Parentheses, Min Stack)

- Queue and Deque Concepts (with real examples)

- When to Use Stack vs Queue in Interviews


Week 5: Trees & Graphs Essentials

- Binary Trees and BST Basics

- Tree Traversals (Inorder, Preorder, Postorder)

- Graph Representations (Adjacency List, Matrix)

- Breadth-First Search (BFS) and Depth-First Search (DFS) explained simply


Week 6: Sorting, Searching & Interview Patterns

- Core Sorting Algorithms (Selection, Bubble, Insertion)

- Advanced Sorting (Merge Sort, Quick Sort)

- Binary Search Patterns (Find First, Last Occurrence, etc.)

- Mastering Interview Patterns (Two Sum, Three Sum, Subarray Sum, etc.)


Week 7: Dynamic Programming & Advanced Problem Solving

- What is Dynamic Programming (DP)?

- Top-Down vs Bottom-Up Approach

- Memoization and Tabulation Explained

- Classic DP Problems (Fibonacci, 0/1 Knapsack, Longest Subsequence)


Week 8: Real-World Mock Interviews

- Solving Medium to Hard Problems

- Tackling FAANG-level Interview Questions

- Tips to Handle Pressure in Coding Rounds

- Building the Right Mindset for Success


React with ❤️ if you're ready for this new coding series


You can join our WhatsApp channel to access it for free: https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X

𝗧𝗵𝗲 𝗯𝗲𝘀𝘁 𝗰𝗼𝗱𝗶𝗻𝗴 𝗹𝗲𝘀𝘀𝗼𝗻 𝘆𝗼𝘂’𝗹𝗹 𝗿𝗲𝗰𝗲𝗶𝘃𝗲 𝘁𝗼𝗱𝗮𝘆:

Master the fundamentals of programming—they are the backbone of every great software you’ll ever build.

-> Variables store your data. Know what you’re holding and why—it’s the first step to clean, readable logic.

-> Conditions & Loops shape the behavior of your code. They allow your programs to make decisions and repeat tasks—smartly and efficiently.

-> Functions are your code’s superpower. Reuse logic, stay DRY (Don’t Repeat Yourself), and build clean, modular systems.'

-> Debugging isn’t a chore—it’s a chance to become a better thinker. Every bug fixed is a lesson learned.

In a world full of users, become a creator. Code to solve, not just to build.

Learn, write, break, fix—and grow.

Always follow best practices:

- Meaningful variable names

- Writing readable, maintainable code

- Testing early and often


One bad habit can cost you hours. One good habit can save you days.

Top 9 Http Methods-

GET 🧐 - Retrieve data from a resource.
HEAD 🎧 - Retrieve the headers of a resource.
POST 📮 - Submit data to a resource.
PUT 📥 - Update an existing resource or create a new resource.
DELETE 🗑️ - Remove a resource.
CONNECT 🔗 - Establish a network connection for a resource.
OPTIONS ⚙️ - Describe communication options for the target resource.
TRACE 🕵️‍♂️ - Retrieve a diagnostic trace of the request.
PATCH 🩹 - Apply a partial update to a resource.

Java vs Python

🚀 Key Skills for Aspiring Tech Specialists

📊 Data Analyst:
- Proficiency in SQL for database querying
- Advanced Excel for data manipulation
- Programming with Python or R for data analysis
- Statistical analysis to understand data trends
- Data visualization tools like Tableau or PowerBI
- Data preprocessing to clean and structure data
- Exploratory data analysis techniques

🧠 Data Scientist:
- Strong knowledge of Python and R for statistical analysis
- Machine learning for predictive modeling
- Deep understanding of mathematics and statistics
- Data wrangling to prepare data for analysis
- Big data platforms like Hadoop or Spark
- Data visualization and communication skills
- Experience with A/B testing frameworks

🏗 Data Engineer:
- Expertise in SQL and NoSQL databases
- Experience with data warehousing solutions
- ETL (Extract, Transform, Load) process knowledge
- Familiarity with big data tools (e.g., Apache Spark)
- Proficient in Python, Java, or Scala
- Knowledge of cloud services like AWS, GCP, or Azure
- Understanding of data pipeline and workflow management tools

🤖 Machine Learning Engineer:
- Proficiency in Python and libraries like scikit-learn, TensorFlow
- Solid understanding of machine learning algorithms
- Experience with neural networks and deep learning frameworks
- Ability to implement models and fine-tune their parameters
- Knowledge of software engineering best practices
- Data modeling and evaluation strategies
- Strong mathematical skills, particularly in linear algebra and calculus

🧠 Deep Learning Engineer:
- Expertise in deep learning frameworks like TensorFlow or PyTorch
- Understanding of Convolutional and Recurrent Neural Networks
- Experience with GPU computing and parallel processing
- Familiarity with computer vision and natural language processing
- Ability to handle large datasets and train complex models
- Research mindset to keep up with the latest developments in deep learning

🤯 AI Engineer:
- Solid foundation in algorithms, logic, and mathematics
- Proficiency in programming languages like Python or C++
- Experience with AI technologies including ML, neural networks, and cognitive computing
- Understanding of AI model deployment and scaling
- Knowledge of AI ethics and responsible AI practices
- Strong problem-solving and analytical skills

🔊 NLP Engineer:
- Background in linguistics and language models
- Proficiency with NLP libraries (e.g., NLTK, spaCy)
- Experience with text preprocessing and tokenization
- Understanding of sentiment analysis, text classification, and named entity recognition
- Familiarity with transformer models like BERT and GPT
- Ability to work with large text datasets and sequential data

🌟 Embrace the world of data and AI, and become the architect of tomorrow's technology!

DSA (Data Structures and Algorithms) Essential Topics for Interviews

1️⃣ Arrays and Strings

Basic operations (insert, delete, update)

Two-pointer technique

Sliding window

Prefix sum

Kadane’s algorithm

Subarray problems


2️⃣ Linked List

Singly & Doubly Linked List

Reverse a linked list

Detect loop (Floyd’s Cycle)

Merge two sorted lists

Intersection of linked lists


3️⃣ Stack & Queue

Stack using array or linked list

Queue and Circular Queue

Monotonic Stack/Queue

LRU Cache (LinkedHashMap/Deque)

Infix to Postfix conversion


4️⃣ Hashing

HashMap, HashSet

Frequency counting

Two Sum problem

Group Anagrams

Longest Consecutive Sequence


5️⃣ Recursion & Backtracking

Base cases and recursive calls

Subsets, permutations

N-Queens problem

Sudoku solver

Word search


6️⃣ Trees & Binary Trees

Traversals (Inorder, Preorder, Postorder)

Height and Diameter

Balanced Binary Tree

Lowest Common Ancestor (LCA)

Serialize & Deserialize Tree


7️⃣ Binary Search Trees (BST)

Search, Insert, Delete

Validate BST

Kth smallest/largest element

Convert BST to DLL


8️⃣ Heaps & Priority Queues

Min Heap / Max Heap

Heapify

Top K elements

Merge K sorted lists

Median in a stream


9️⃣ Graphs

Representations (adjacency list/matrix)

DFS, BFS

Cycle detection (directed & undirected)

Topological Sort

Dijkstra’s & Bellman-Ford algorithm

Union-Find (Disjoint Set)


10️⃣ Dynamic Programming (DP)

0/1 Knapsack

Longest Common Subsequence

Matrix Chain Multiplication

DP on subsequences

Memoization vs Tabulation


11️⃣ Greedy Algorithms

Activity selection

Huffman coding

Fractional knapsack

Job scheduling


12️⃣ Tries

Insert and search a word

Word search

Auto-complete feature


13️⃣ Bit Manipulation

XOR, AND, OR basics

Check if power of 2

Single Number problem

Count set bits

Coding Interview Resources: https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X

ENJOY LEARNING 👍👍