Dear software engineers,
It stings when you see your college friends or ex-teammates posting about new job offers, hikes, or “finally made it to FAANG” while you’re still hustling for your shot.
Every “I’m thrilled to announce…” on LinkedIn can feel like salt in the wound.
And it’s natural to wonder:
>> Why not me?
>> Am I not good enough?
>> Will my turn ever come?
But please understand that everyone’s journey in tech runs on a different timeline.
Some folks have been grinding DSA or building side projects for years.
Some get lucky with a referral or the right timing.
None of it means you’re lagging behind, or that you don’t deserve that shot.
You might feel stuck now, but your breakthrough might just be around the corner.
Keep building, keep learning, keep shipping, even if it’s lonely.
One day, you’ll look back and realize this phase taught you resilience, focus, and the kind of grit you can’t learn in any bootcamp.
It stings when you see your college friends or ex-teammates posting about new job offers, hikes, or “finally made it to FAANG” while you’re still hustling for your shot.
Every “I’m thrilled to announce…” on LinkedIn can feel like salt in the wound.
And it’s natural to wonder:
>> Why not me?
>> Am I not good enough?
>> Will my turn ever come?
But please understand that everyone’s journey in tech runs on a different timeline.
Some folks have been grinding DSA or building side projects for years.
Some get lucky with a referral or the right timing.
None of it means you’re lagging behind, or that you don’t deserve that shot.
You might feel stuck now, but your breakthrough might just be around the corner.
Keep building, keep learning, keep shipping, even if it’s lonely.
One day, you’ll look back and realize this phase taught you resilience, focus, and the kind of grit you can’t learn in any bootcamp.
❤12
Here are 40 most asked DSA questions to ace your next interview -
𝗗𝘆𝗻𝗮𝗺𝗶𝗰 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 (𝗗𝗣):
1. How do you find the nth Fibonacci number using dynamic programming?
2. Write a dynamic programming solution for the 0/1 knapsack problem.
3. Memoization to optimize recursive solutions in dynamic programming?
4. Implement a dynamic programming algorithm to find the longest common subsequence of two strings.
5. The coin change problem.
6. Tabulation approach in dynamic programming.
𝗕𝗮𝗰𝗸𝘁𝗿𝗮𝗰𝗸𝗶𝗻𝗴:
7. Backtracking algorithm to solve the N-Queens problem.
8. Generate all permutations of a given set using backtracking?
9. Implement backtracking to solve the Sudoku puzzle.
10. Subset sum problem.
11. Graph coloring problem using backtracking.
12. Write a backtracking algorithm to find the Hamiltonian cycle in a graph.
𝗛𝗮𝘀𝗵𝗶𝗻𝗴:
13. Implement a hash table using separate chaining.
14. First non-repeating character in a string using hashing.
15. Collision resolution techniques in hashing.
16. Write a function to solve the two-sum problem using hashing.
17. How can you implement a hash set data structure?
18. Count the frequency of elements in an array using hashing.
𝗛𝗲𝗮𝗽:
19. Implement a priority queue using a min-heap.
20. How do you merge K sorted arrays using a min-heap?
21. Write a function to perform heap sort algorithm.
22. Find the kth largest element in an array using a min-heap.
23. Implement a priority queue using a min-heap.
24. How do you build a max heap from an array?
𝗧𝗿𝗶𝗲𝘀:
25. Implement a trie data structure.
26. Write a function to search for a word in a trie.
27. How can you implement autocomplete feature using a trie?
28. Deleting a word from a trie.
30. Write a function to find all words matching a pattern in a trie.
𝗚𝗿𝗲𝗲𝗱𝘆 𝗔𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺𝘀:
31. Solve the activity selection problem using a greedy algorithm.
32. Implement Huffman coding using a greedy algorithm.
33. Write a function to find the minimum spanning tree using Prim's algorithm.
34. Coin change problem.
35. Dijkstra's algorithm using a greedy approach.
36. Implement the job sequencing problem using a greedy algorithm.
37. Stack Vs queue.
38. breadth-first search (BFS) and depth-first search (DFS) traversal
39. Concept of big O notation.
40. What is an AVL tree? Explain its properties and how it maintains balance during insertion and deletion operations.
React ❤️ for more
𝗗𝘆𝗻𝗮𝗺𝗶𝗰 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 (𝗗𝗣):
1. How do you find the nth Fibonacci number using dynamic programming?
2. Write a dynamic programming solution for the 0/1 knapsack problem.
3. Memoization to optimize recursive solutions in dynamic programming?
4. Implement a dynamic programming algorithm to find the longest common subsequence of two strings.
5. The coin change problem.
6. Tabulation approach in dynamic programming.
𝗕𝗮𝗰𝗸𝘁𝗿𝗮𝗰𝗸𝗶𝗻𝗴:
7. Backtracking algorithm to solve the N-Queens problem.
8. Generate all permutations of a given set using backtracking?
9. Implement backtracking to solve the Sudoku puzzle.
10. Subset sum problem.
11. Graph coloring problem using backtracking.
12. Write a backtracking algorithm to find the Hamiltonian cycle in a graph.
𝗛𝗮𝘀𝗵𝗶𝗻𝗴:
13. Implement a hash table using separate chaining.
14. First non-repeating character in a string using hashing.
15. Collision resolution techniques in hashing.
16. Write a function to solve the two-sum problem using hashing.
17. How can you implement a hash set data structure?
18. Count the frequency of elements in an array using hashing.
𝗛𝗲𝗮𝗽:
19. Implement a priority queue using a min-heap.
20. How do you merge K sorted arrays using a min-heap?
21. Write a function to perform heap sort algorithm.
22. Find the kth largest element in an array using a min-heap.
23. Implement a priority queue using a min-heap.
24. How do you build a max heap from an array?
𝗧𝗿𝗶𝗲𝘀:
25. Implement a trie data structure.
26. Write a function to search for a word in a trie.
27. How can you implement autocomplete feature using a trie?
28. Deleting a word from a trie.
30. Write a function to find all words matching a pattern in a trie.
𝗚𝗿𝗲𝗲𝗱𝘆 𝗔𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺𝘀:
31. Solve the activity selection problem using a greedy algorithm.
32. Implement Huffman coding using a greedy algorithm.
33. Write a function to find the minimum spanning tree using Prim's algorithm.
34. Coin change problem.
35. Dijkstra's algorithm using a greedy approach.
36. Implement the job sequencing problem using a greedy algorithm.
37. Stack Vs queue.
38. breadth-first search (BFS) and depth-first search (DFS) traversal
39. Concept of big O notation.
40. What is an AVL tree? Explain its properties and how it maintains balance during insertion and deletion operations.
React ❤️ for more
❤2
These are top 5 data structures and algorithms projects, allowing you to dive deep into the world of DSA 💪🏻
•Project 1: Snakes Game (Arrays)
The Snakes Game project is a classic implementation of the popular game
Snake.
This project allows you to understand the concepts of arrays, loops, and conditional statements. You can further enhance the game by incorporating additional features such as score tracking and power-ups.
•Project 2: Cash Flow Minimizer (Graphs/ Multisets/Heaps)
The Cash Flow Minimizer project involves solving a cash flow optimization problem using graphs, multisets, and heaps. Given a set of transactions among a group of people, the objective is to minimize the total number of transactions required to settle all debts
•Project 3: Sudoku Solver (Backtracking)
The Sudoku Solver project aims to solve the popular Sudoku puzzle using backtracking. This project allows you to understand the backtracking algorithm, which is widely used in solving constraint satisfaction problems.
•Project 4: File Zipper (Greedy Huffman
Encoder)
The File Zipper project focuses on implementing a file compression utility using the Greedy Huffman encoding algorithm. This project provides a practical application of the greedy algorithm and helps you understand the trade-offs between
compression ratio and execution time.
•Project 5: Map Navigator (Dijkstra’s
Algorithm)
The Map Navigator project aims to develop a navigation system using Dijkstra’s algorithm. It involves finding the shortest path between two locations on a map, considering factors such as distance and traffic.
You can check these amazing resources for DSA Preparation
Join for more: https://t.iss.one/crackingthecodinginterview
All the best 👍👍
•Project 1: Snakes Game (Arrays)
The Snakes Game project is a classic implementation of the popular game
Snake.
This project allows you to understand the concepts of arrays, loops, and conditional statements. You can further enhance the game by incorporating additional features such as score tracking and power-ups.
•Project 2: Cash Flow Minimizer (Graphs/ Multisets/Heaps)
The Cash Flow Minimizer project involves solving a cash flow optimization problem using graphs, multisets, and heaps. Given a set of transactions among a group of people, the objective is to minimize the total number of transactions required to settle all debts
•Project 3: Sudoku Solver (Backtracking)
The Sudoku Solver project aims to solve the popular Sudoku puzzle using backtracking. This project allows you to understand the backtracking algorithm, which is widely used in solving constraint satisfaction problems.
•Project 4: File Zipper (Greedy Huffman
Encoder)
The File Zipper project focuses on implementing a file compression utility using the Greedy Huffman encoding algorithm. This project provides a practical application of the greedy algorithm and helps you understand the trade-offs between
compression ratio and execution time.
•Project 5: Map Navigator (Dijkstra’s
Algorithm)
The Map Navigator project aims to develop a navigation system using Dijkstra’s algorithm. It involves finding the shortest path between two locations on a map, considering factors such as distance and traffic.
You can check these amazing resources for DSA Preparation
Join for more: https://t.iss.one/crackingthecodinginterview
All the best 👍👍
❤2
✅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
Join this coding WhatsApp group 👇 You will thank me later 😊👇
https://whatsapp.com/channel/0029VahiFZQ4o7qN54LTzB17
https://whatsapp.com/channel/0029VahiFZQ4o7qN54LTzB17
❤2👍1
Top Libraries & Frameworks by Language 📚💻
❯ Python
• Pandas ➟ Data Analysis
• NumPy ➟ Math & Arrays
• Scikit-learn ➟ Machine Learning
• TensorFlow / PyTorch ➟ Deep Learning
• Flask / Django ➟ Web Development
• OpenCV ➟ Image Processing
❯ JavaScript / TypeScript
• React ➟ UI Development
• Vue ➟ Lightweight SPAs
• Angular ➟ Enterprise Apps
• Next.js ➟ Full-Stack Web
• Express ➟ Backend APIs
• Three.js ➟ 3D Web Graphics
❯ Java
• Spring Boot ➟ Microservices
• Hibernate ➟ ORM
• Apache Maven ➟ Build Automation
• Apache Kafka ➟ Real-Time Data
❯ C++
• Boost ➟ Utility Libraries
• Qt ➟ GUI Applications
• Unreal Engine ➟ Game Development
❯ C#
• .NET / ASP.NET ➟ Web Apps
• Unity ➟ Game Development
• Entity Framework ➟ ORM
❯ R
• ggplot2 ➟ Data Visualization
• dplyr ➟ Data Manipulation
• caret ➟ Machine Learning
• Shiny ➟ Interactive Dashboards
❯ PHP
• Laravel ➟ Full-Stack Web
• Symfony ➟ Web Framework
• PHPUnit ➟ Testing
❯ Go (Golang)
• Gin ➟ Web Framework
• Gorilla ➟ Web Toolkit
• GORM ➟ ORM for Go
❯ Rust
• Actix ➟ Web Framework
• Rocket ➟ Web Development
• Tokio ➟ Async Runtime
Coding Resources: https://whatsapp.com/channel/0029VahiFZQ4o7qN54LTzB17
React with ❤️ for more useful content
❯ Python
• Pandas ➟ Data Analysis
• NumPy ➟ Math & Arrays
• Scikit-learn ➟ Machine Learning
• TensorFlow / PyTorch ➟ Deep Learning
• Flask / Django ➟ Web Development
• OpenCV ➟ Image Processing
❯ JavaScript / TypeScript
• React ➟ UI Development
• Vue ➟ Lightweight SPAs
• Angular ➟ Enterprise Apps
• Next.js ➟ Full-Stack Web
• Express ➟ Backend APIs
• Three.js ➟ 3D Web Graphics
❯ Java
• Spring Boot ➟ Microservices
• Hibernate ➟ ORM
• Apache Maven ➟ Build Automation
• Apache Kafka ➟ Real-Time Data
❯ C++
• Boost ➟ Utility Libraries
• Qt ➟ GUI Applications
• Unreal Engine ➟ Game Development
❯ C#
• .NET / ASP.NET ➟ Web Apps
• Unity ➟ Game Development
• Entity Framework ➟ ORM
❯ R
• ggplot2 ➟ Data Visualization
• dplyr ➟ Data Manipulation
• caret ➟ Machine Learning
• Shiny ➟ Interactive Dashboards
❯ PHP
• Laravel ➟ Full-Stack Web
• Symfony ➟ Web Framework
• PHPUnit ➟ Testing
❯ Go (Golang)
• Gin ➟ Web Framework
• Gorilla ➟ Web Toolkit
• GORM ➟ ORM for Go
❯ Rust
• Actix ➟ Web Framework
• Rocket ➟ Web Development
• Tokio ➟ Async Runtime
Coding Resources: https://whatsapp.com/channel/0029VahiFZQ4o7qN54LTzB17
React with ❤️ for more useful content
❤5
💻 Popular Coding Languages & Their Uses 🚀
There are many programming languages, each serving different purposes. Here are some key ones you should know:
🔹 1. Python – Beginner-friendly, versatile, and widely used in data science, AI, web development, and automation.
🔹 2. JavaScript – Essential for frontend and backend web development, powering interactive websites and applications.
🔹 3. Java – Used for enterprise applications, Android development, and large-scale systems due to its stability.
🔹 4. C++ – High-performance language ideal for game development, operating systems, and embedded systems.
🔹 5. C# – Commonly used in game development (Unity), Windows applications, and enterprise software.
🔹 6. Swift – The go-to language for iOS and macOS development, known for its efficiency.
🔹 7. Go (Golang) – Designed for high-performance applications, cloud computing, and network programming.
🔹 8. Rust – Focuses on memory safety and performance, making it great for system-level programming.
🔹 9. SQL – Essential for database management, allowing efficient data retrieval and manipulation.
🔹 10. Kotlin – Popular for Android app development, offering modern features compared to Java.
🔥 React ❤️ for more 😊🚀
There are many programming languages, each serving different purposes. Here are some key ones you should know:
🔹 1. Python – Beginner-friendly, versatile, and widely used in data science, AI, web development, and automation.
🔹 2. JavaScript – Essential for frontend and backend web development, powering interactive websites and applications.
🔹 3. Java – Used for enterprise applications, Android development, and large-scale systems due to its stability.
🔹 4. C++ – High-performance language ideal for game development, operating systems, and embedded systems.
🔹 5. C# – Commonly used in game development (Unity), Windows applications, and enterprise software.
🔹 6. Swift – The go-to language for iOS and macOS development, known for its efficiency.
🔹 7. Go (Golang) – Designed for high-performance applications, cloud computing, and network programming.
🔹 8. Rust – Focuses on memory safety and performance, making it great for system-level programming.
🔹 9. SQL – Essential for database management, allowing efficient data retrieval and manipulation.
🔹 10. Kotlin – Popular for Android app development, offering modern features compared to Java.
🔥 React ❤️ for more 😊🚀
❤5
🔰 Frontend Web Development Roadmap 2025 (With Mini Projects)
├── 🧠 Basics of How the Web Works (HTTP, DNS, Hosting)
├── 📄 HTML5 (Structure, Forms, Media)
├── 🎨 CSS3 (Box Model, Flexbox, Grid, Animations)
├── 🖱 Mini Project: Personal Portfolio Website
├── ⚡️ JavaScript Fundamentals (Events, DOM, Arrays, Functions)
├── 🧪 Mini Project: Interactive Quiz App
├── ⚙️ Version Control with Git & GitHub
├── 📱 Responsive Design with Media Queries
├── 🧪 Mini Project: Responsive Blog Homepage
├── 📦 Introduction to NPM, VS Code Shortcuts, Emmet
├── ⚛ Intro to Frontend Frameworks: React/Vue
Frontend Development Resources: https://whatsapp.com/channel/0029VaxfCpv2v1IqQjv6Ke0r
ENJOY LEARNING 👍👍
├── 🧠 Basics of How the Web Works (HTTP, DNS, Hosting)
├── 📄 HTML5 (Structure, Forms, Media)
├── 🎨 CSS3 (Box Model, Flexbox, Grid, Animations)
├── 🖱 Mini Project: Personal Portfolio Website
├── ⚡️ JavaScript Fundamentals (Events, DOM, Arrays, Functions)
├── 🧪 Mini Project: Interactive Quiz App
├── ⚙️ Version Control with Git & GitHub
├── 📱 Responsive Design with Media Queries
├── 🧪 Mini Project: Responsive Blog Homepage
├── 📦 Introduction to NPM, VS Code Shortcuts, Emmet
├── ⚛ Intro to Frontend Frameworks: React/Vue
Frontend Development Resources: https://whatsapp.com/channel/0029VaxfCpv2v1IqQjv6Ke0r
ENJOY LEARNING 👍👍
❤4
If I wanted to get my opportunity to interview at Google or Amazon for SDE roles in the next 6-8 months…
Here’s exactly how I’d approach it (I’ve taught this to 100s of students and followed it myself to land interviews at 3+ FAANGs):
► Step 1: Learn to Code (from scratch, even if you’re from non-CS background)
I helped my sister go from zero coding knowledge (she studied Biology and Electrical Engineering) to landing a job at Microsoft.
We started with:
- A simple programming language (C++, Java, Python — pick one)
- FreeCodeCamp on YouTube for beginner-friendly lectures
- Key rule: Don’t just watch. Code along with the video line by line.
Time required: 30–40 days to get good with loops, conditions, syntax.
► Step 2: Start with DSA before jumping to development
Why?
- 90% of tech interviews in top companies focus on Data Structures & Algorithms
- You’ll need time to master it, so start early.
Start with:
- Arrays → Linked List → Stacks → Queues
- You can follow the DSA videos on my channel.
- Practice while learning is a must.
► Step 3: Follow a smart topic order
Once you’re done with basics, follow this path:
1. Searching & Sorting
2. Recursion & Backtracking
3. Greedy
4. Sliding Window & Two Pointers
5. Trees & Graphs
6. Dynamic Programming
7. Tries, Heaps, and Union Find
Make revision notes as you go — note down how you solved each question, what tricks worked, and how you optimized it.
► Step 4: Start giving contests (don’t wait till you’re “ready”)
Most students wait to “finish DSA” before attempting contests.
That’s a huge mistake.
Contests teach you:
- Time management under pressure
- Handling edge cases
- Thinking fast
Platforms: LeetCode Weekly/ Biweekly, Codeforces, AtCoder, etc.
And after every contest, do upsolving — solve the questions you couldn’t during the contest.
► Step 5: Revise smart
Create a “Revision Sheet” with 100 key problems you’ve solved and want to reattempt.
Every 2-3 weeks, pick problems randomly and solve again without seeing solutions.
This trains your recall + improves your clarity.
Coding Projects:👇
https://whatsapp.com/channel/0029VazkxJ62UPB7OQhBE502
ENJOY LEARNING 👍👍
Here’s exactly how I’d approach it (I’ve taught this to 100s of students and followed it myself to land interviews at 3+ FAANGs):
► Step 1: Learn to Code (from scratch, even if you’re from non-CS background)
I helped my sister go from zero coding knowledge (she studied Biology and Electrical Engineering) to landing a job at Microsoft.
We started with:
- A simple programming language (C++, Java, Python — pick one)
- FreeCodeCamp on YouTube for beginner-friendly lectures
- Key rule: Don’t just watch. Code along with the video line by line.
Time required: 30–40 days to get good with loops, conditions, syntax.
► Step 2: Start with DSA before jumping to development
Why?
- 90% of tech interviews in top companies focus on Data Structures & Algorithms
- You’ll need time to master it, so start early.
Start with:
- Arrays → Linked List → Stacks → Queues
- You can follow the DSA videos on my channel.
- Practice while learning is a must.
► Step 3: Follow a smart topic order
Once you’re done with basics, follow this path:
1. Searching & Sorting
2. Recursion & Backtracking
3. Greedy
4. Sliding Window & Two Pointers
5. Trees & Graphs
6. Dynamic Programming
7. Tries, Heaps, and Union Find
Make revision notes as you go — note down how you solved each question, what tricks worked, and how you optimized it.
► Step 4: Start giving contests (don’t wait till you’re “ready”)
Most students wait to “finish DSA” before attempting contests.
That’s a huge mistake.
Contests teach you:
- Time management under pressure
- Handling edge cases
- Thinking fast
Platforms: LeetCode Weekly/ Biweekly, Codeforces, AtCoder, etc.
And after every contest, do upsolving — solve the questions you couldn’t during the contest.
► Step 5: Revise smart
Create a “Revision Sheet” with 100 key problems you’ve solved and want to reattempt.
Every 2-3 weeks, pick problems randomly and solve again without seeing solutions.
This trains your recall + improves your clarity.
Coding Projects:👇
https://whatsapp.com/channel/0029VazkxJ62UPB7OQhBE502
ENJOY LEARNING 👍👍
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