When to Use Which Programming Language?
C ➝ OS Development, Embedded Systems, Game Engines
C++ ➝ Game Dev, High-Performance Apps, Finance
Java ➝ Enterprise Apps, Android, Backend
C# ➝ Unity Games, Windows Apps
Python ➝ AI/ML, Data, Automation, Web Dev
JavaScript ➝ Frontend, Full-Stack, Web Games
Golang ➝ Cloud Services, APIs, Networking
Swift ➝ iOS/macOS Apps
Kotlin ➝ Android, Backend
PHP ➝ Web Dev (WordPress, Laravel)
Ruby ➝ Web Dev (Rails), Prototypes
Rust ➝ System Apps, Blockchain, HPC
Lua ➝ Game Scripting (Roblox, WoW)
R ➝ Stats, Data Science, Bioinformatics
SQL ➝ Data Analysis, DB Management
TypeScript ➝ Scalable Web Apps
Node.js ➝ Backend, Real-Time Apps
React ➝ Modern Web UIs
Vue ➝ Lightweight SPAs
Django ➝ AI/ML Backend, Web Dev
Laravel ➝ Full-Stack PHP
Blazor ➝ Web with .NET
Spring Boot ➝ Microservices, Java Enterprise
Ruby on Rails ➝ MVPs, Startups
HTML/CSS ➝ UI/UX, Web Design
Git ➝ Version Control
Linux ➝ Server, Security, DevOps
DevOps ➝ Infra Automation, CI/CD
CI/CD ➝ Testing + Deployment
Docker ➝ Containerization
Kubernetes ➝ Cloud Orchestration
Microservices ➝ Scalable Backends
Selenium ➝ Web Testing
Playwright ➝ Modern Web Automation
Credits: https://whatsapp.com/channel/0029VahiFZQ4o7qN54LTzB17
ENJOY LEARNING 👍👍
C ➝ OS Development, Embedded Systems, Game Engines
C++ ➝ Game Dev, High-Performance Apps, Finance
Java ➝ Enterprise Apps, Android, Backend
C# ➝ Unity Games, Windows Apps
Python ➝ AI/ML, Data, Automation, Web Dev
JavaScript ➝ Frontend, Full-Stack, Web Games
Golang ➝ Cloud Services, APIs, Networking
Swift ➝ iOS/macOS Apps
Kotlin ➝ Android, Backend
PHP ➝ Web Dev (WordPress, Laravel)
Ruby ➝ Web Dev (Rails), Prototypes
Rust ➝ System Apps, Blockchain, HPC
Lua ➝ Game Scripting (Roblox, WoW)
R ➝ Stats, Data Science, Bioinformatics
SQL ➝ Data Analysis, DB Management
TypeScript ➝ Scalable Web Apps
Node.js ➝ Backend, Real-Time Apps
React ➝ Modern Web UIs
Vue ➝ Lightweight SPAs
Django ➝ AI/ML Backend, Web Dev
Laravel ➝ Full-Stack PHP
Blazor ➝ Web with .NET
Spring Boot ➝ Microservices, Java Enterprise
Ruby on Rails ➝ MVPs, Startups
HTML/CSS ➝ UI/UX, Web Design
Git ➝ Version Control
Linux ➝ Server, Security, DevOps
DevOps ➝ Infra Automation, CI/CD
CI/CD ➝ Testing + Deployment
Docker ➝ Containerization
Kubernetes ➝ Cloud Orchestration
Microservices ➝ Scalable Backends
Selenium ➝ Web Testing
Playwright ➝ Modern Web Automation
Credits: https://whatsapp.com/channel/0029VahiFZQ4o7qN54LTzB17
ENJOY LEARNING 👍👍
👍4
𝗣𝘆𝘁𝗵𝗼𝗻 𝗟𝗶𝘀𝘁 𝗠𝗲𝘁𝗵𝗼𝗱𝘀 𝗖𝗵𝗲𝗮𝘁 𝗦𝗵𝗲𝗲𝘁
𝟭. 𝗮𝗽𝗽𝗲𝗻𝗱( ) – Adds an element to the end of the list.
𝟮. 𝗰𝗼𝘂𝗻𝘁( ) – Returns the number of occurrences of a specific element.
𝟯. 𝗰𝗼𝗽𝘆( ) – Creates a duplicate of the list.
𝟰. 𝗶𝗻𝗱𝗲𝘅( ) – Returns the position of the first occurrence of an element.
𝟱. 𝗶𝗻𝘀𝗲𝗿𝘁(𝟭, ) – Inserts an element at a specified index.
𝟲. 𝗿𝗲𝘃𝗲𝗿𝘀𝗲( ) – Reverses the order of elements in the list.
𝟳. 𝗽𝗼𝗽( ) – Removes and returns the last element.
𝟴. 𝗰𝗹𝗲𝗮𝗿( ) – Removes all elements from the list.
𝟵. 𝗽𝗼𝗽(𝟭) – Removes and returns the element at index 1.
Master these list methods to handle Python lists efficiently! 🚀
𝟭. 𝗮𝗽𝗽𝗲𝗻𝗱( ) – Adds an element to the end of the list.
𝟮. 𝗰𝗼𝘂𝗻𝘁( ) – Returns the number of occurrences of a specific element.
𝟯. 𝗰𝗼𝗽𝘆( ) – Creates a duplicate of the list.
𝟰. 𝗶𝗻𝗱𝗲𝘅( ) – Returns the position of the first occurrence of an element.
𝟱. 𝗶𝗻𝘀𝗲𝗿𝘁(𝟭, ) – Inserts an element at a specified index.
𝟲. 𝗿𝗲𝘃𝗲𝗿𝘀𝗲( ) – Reverses the order of elements in the list.
𝟳. 𝗽𝗼𝗽( ) – Removes and returns the last element.
𝟴. 𝗰𝗹𝗲𝗮𝗿( ) – Removes all elements from the list.
𝟵. 𝗽𝗼𝗽(𝟭) – Removes and returns the element at index 1.
Master these list methods to handle Python lists efficiently! 🚀
👍2❤1
Top 10 Python Concepts
Variables & Data Types
Understand integers, floats, strings, booleans, lists, tuples, sets, and dictionaries.
Control Flow (if, else, elif)
Write logic-based programs using conditional statements.
Loops (for & while)
Automate tasks and iterate over data efficiently.
Functions
Build reusable code blocks with def, understand parameters, return values, and scope.
List Comprehensions
Create and transform lists concisely:
[x*2 for x in range(10) if x % 2 == 0]
Modules & Packages
Import built-in, third-party, or custom modules to structure your code.
Exception Handling
Handle errors using try, except, finally for robust programs.
Object-Oriented Programming (OOP)
Learn classes, objects, inheritance, encapsulation, and polymorphism.
File Handling
Open, read, write, and manage files using open(), read(), write().
Working with Libraries
Use powerful libraries like:
- NumPy for numerical operations
- Pandas for data analysis
- Matplotlib/Seaborn for visualization
- Requests for API calls
- JSON for data parsing
#python
Variables & Data Types
Understand integers, floats, strings, booleans, lists, tuples, sets, and dictionaries.
Control Flow (if, else, elif)
Write logic-based programs using conditional statements.
Loops (for & while)
Automate tasks and iterate over data efficiently.
Functions
Build reusable code blocks with def, understand parameters, return values, and scope.
List Comprehensions
Create and transform lists concisely:
[x*2 for x in range(10) if x % 2 == 0]
Modules & Packages
Import built-in, third-party, or custom modules to structure your code.
Exception Handling
Handle errors using try, except, finally for robust programs.
Object-Oriented Programming (OOP)
Learn classes, objects, inheritance, encapsulation, and polymorphism.
File Handling
Open, read, write, and manage files using open(), read(), write().
Working with Libraries
Use powerful libraries like:
- NumPy for numerical operations
- Pandas for data analysis
- Matplotlib/Seaborn for visualization
- Requests for API calls
- JSON for data parsing
#python
👍4
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>
✅ Best Telegram channels to get free coding & data science resources
https://t.me/addlist/4q2PYC0pH_VjZDk5
✅ Free Courses with Certificate:
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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>
✅ Best Telegram channels to get free coding & data science resources
https://t.me/addlist/4q2PYC0pH_VjZDk5
✅ Free Courses with Certificate:
https://t.me/free4unow_backup
👍2❤1
Join our WhatsApp channel to test your coding knowledge
👇👇
https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X
👇👇
https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X
❤1
✅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 👍👍
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 👍👍
👍4❤2
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 👍👍
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 👍👍
👍1
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
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
❤4👍2
🔰 Javascript cheat sheet
This is the latest Javascript cheat sheet. Save it and share with your friends.
It contain variables, data types, operators, functions, conditional statements, loops and DOM manipulation
This is the latest Javascript cheat sheet. Save it and share with your friends.
It contain variables, data types, operators, functions, conditional statements, loops and DOM manipulation
👍2❤1
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.
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.
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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.
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.
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