Coding Interview Resources
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This channel contains the free resources and solution of coding problems which are usually asked in the interviews.

Managed by: @love_data
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๐Ÿ“Š ๐—•๐˜‚๐—ถ๐—น๐—ฑ ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜€๐˜ ๐—ฃ๐—ผ๐—ฟ๐˜๐—ณ๐—ผ๐—น๐—ถ๐—ผ | ๐Ÿฑ ๐—›๐—ฎ๐—ป๐—ฑ๐˜€-๐—ข๐—ป ๐—ฃ๐—ฟ๐—ผ๐—ท๐—ฒ๐—ฐ๐˜๐˜€ ๐Ÿš€

Learning Data Analytics? Don't stop with tutorials โ€” build real projects that you can showcase on your resume and portfolio! ๐Ÿ’ป

๐Ÿ”ฅ Practice with 5 Hands-On Projects covering:

๐Ÿ—„๏ธ SQL
๐Ÿ“Š Excel
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๐Ÿ”—๐—Ÿ๐—ถ๐—ป๐—ธ ๐Ÿ‘‡:- 

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๐ŸŽ“ Perfect for Students | Freshers | Data Analyst Aspirants | Beginners
โค1๐Ÿ‘1
๐Ÿš€ ๐Ÿฐ ๐—™๐—ฅ๐—˜๐—˜ ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐˜๐—ผ ๐—•๐—ผ๐—ผ๐˜€๐˜ ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐—ฅ๐—ฒ๐˜€๐˜‚๐—บ๐—ฒ & ๐—–๐—ผ๐—ป๐—ณ๐—ถ๐—ฑ๐—ฒ๐—ป๐—ฐ๐—ฒ ๐ŸŽ“๐Ÿ”ฅ

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โค1
โœ… Top 50 DSA (Data Structures & Algorithms) Interview Questions ๐Ÿ“šโš™๏ธ

1. What is a Data Structure?
2. What are the different types of data structures?
3. What is the difference between Array and Linked List?
4. How does a Stack work?
5. What is a Queue? Difference between Queue and Deque?
6. What is a Priority Queue?
7. What is a Hash Table and how does it work?
8. What is the difference between HashMap and HashSet?
9. What are Trees? Explain Binary Tree.
10. What is a Binary Search Tree (BST)?
11. What is the difference between BFS and DFS?
12. What is a Heap?
13. What is a Trie?
14. What is a Graph?
15. Difference between Directed and Undirected Graph?
16. What is the time complexity of common operations in arrays and linked lists?
17. What is recursion?
18. What are base case and recursive case?
19. What is dynamic programming?
20. Difference between Memoization and Tabulation?
21. What is the Sliding Window technique?
22. Explain Two-Pointer technique.
23. What is the Binary Search algorithm?
24. What is the Merge Sort algorithm?
25. What is the Quick Sort algorithm?
26. Difference between Merge Sort and Quick Sort?
27. What is Insertion Sort and how does it work?
28. What is Selection Sort?
29. What is Bubble Sort and its drawbacks?
30. What is the time and space complexity of sorting algorithms?
31. What is Backtracking?
32. Explain the N-Queens Problem.
33. What is the Kadane's Algorithm?
34. What is Floydโ€™s Cycle Detection Algorithm?
35. What is the Union-Find (Disjoint Set) algorithm?
36. What are topological sorting and its uses?
37. What is Dijkstra's Algorithm?
38. What is Bellman-Ford Algorithm?
39. What is Kruskalโ€™s Algorithm?
40. What is Primโ€™s Algorithm?
41. What is Longest Common Subsequence (LCS)?
42. What is Longest Increasing Subsequence (LIS)?
43. What is a Palindrome Substring problem?
44. What is the difference between greedy and dynamic programming?
45. What is Big-O notation?
46. What is the difference between time and space complexity?
47. How to find the time complexity of a recursive function?
48. What are amortized time complexities?
49. What is tail recursion?
50. How do you approach solving a coding problem in interviews?

๐Ÿ’ฌ Tap โค๏ธ for the detailed answers!
โค12
๐Ÿ’ป ๐— ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ ๐—ฆ๐—ค๐—Ÿ ๐—ณ๐—ผ๐—ฟ ๐—™๐—ฅ๐—˜๐—˜ | ๐Ÿฑ ๐—•๐—ฒ๐˜€๐˜ ๐—ฌ๐—ผ๐˜‚๐—ง๐˜‚๐—ฏ๐—ฒ ๐—–๐—ต๐—ฎ๐—ป๐—ป๐—ฒ๐—น๐˜€ ๐Ÿš€

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โค1
๐—™๐—ฅ๐—˜๐—˜ ๐— ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ๐—ฐ๐—น๐—ฎ๐˜€๐˜€ ๐—ข๐—ป ๐—Ÿ๐—ฎ๐˜๐—ฒ๐˜€๐˜ ๐—ง๐—ฒ๐—ฐ๐—ต๐—ป๐—ผ๐—น๐—ผ๐—ด๐—ถ๐—ฒ๐˜€ ๐Ÿ˜
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โ€‹
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โ€‹
(Only few slots left )
โ€‹
Date & Time :- 18th August 2026 & 7PM
Sharing a template to request for a job referral on LinkedIn, customize as per your requirement ๐Ÿ‘‡๐Ÿ‘‡

โ
Hey [HR Name],

Hope you're doing well. Iโ€™m alumni from [college-Name]. Expressing my interest in recent 'Sr Data Analyst' role (JobID- 0108) at XYZ-Company. I've 1+ years of relevant experience in data analytics. Would you be open to give me a referral? Looking forward to your response.


(Tap to copy)
โค1
๐Ÿ“Š ๐Ÿฑ ๐—•๐—ฒ๐˜€๐˜ ๐—Ÿ๐—ฒ๐—ฎ๐—ฟ๐—ป๐—ถ๐—ป๐—ด ๐—ฅ๐—ฒ๐˜€๐—ผ๐˜‚๐—ฟ๐—ฐ๐—ฒ๐˜€ ๐—ง๐—ผ ๐— ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ ๐— ๐—ฆ ๐—˜๐˜…๐—ฐ๐—ฒ๐—น ๐—ณ๐—ผ๐—ฟ ๐—™๐—ฅ๐—˜๐—˜

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๐Ÿš€ ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ ๐Ÿ“Š๐Ÿ”ฅ

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๐Ÿ”— ๐—•๐—ผ๐—ผ๐—ธ ๐—ฎ ๐—™๐—ฅ๐—˜๐—˜ ๐—–๐—ฎ๐—ฟ๐—ฒ๐—ฒ๐—ฟ ๐—–๐—ผ๐˜‚๐—ป๐˜€๐—ฒ๐—น๐—น๐—ถ๐—ป๐—ด๐Ÿ‘‡:-

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๐ŸŽ“ Perfect for Students | Freshers | Working Professionals | Career Switchers
๐Ÿš€ Complete Roadmap to Become a Software Developer ๐Ÿ‘จโ€๐Ÿ’ป

Programming teaches you how to code.
Software Development teaches you how to build real-world applications that companies hire for.

Here's the complete roadmap:

๐Ÿง  STEP 1: Software Development Fundamentals

โœ” Software Development Life Cycle (SDLC)

โœ” Types of Software

โœ” Development Methodologies

โœ” Agile & Scrum Basics

๐Ÿ’ป STEP 2: Master One Programming Language

โœ” Language Features

โœ” Best Practices

โœ” Design Patterns

โœ” Clean Code Principles

๐Ÿ—๏ธ STEP 3: Software Architecture

โœ” Monolithic Architecture

โœ” Microservices

โœ” REST APIs

โœ” System Design Basics

๐Ÿ—„๏ธ STEP 4: Databases & Backend

โœ” SQL & NoSQL

โœ” Database Design

โœ” Authentication

โœ” API Development

๐ŸŒ STEP 5: Frontend Development

โœ” HTML

โœ” CSS

โœ” JavaScript

โœ” React

โœ” Responsive Design

โ˜๏ธ STEP 6: DevOps & Cloud

โœ” Git & GitHub

โœ” Docker

โœ” Kubernetes

โœ” AWS / Azure

โœ” CI/CD Pipelines

๐Ÿงช STEP 7: Testing & Debugging

โœ” Unit Testing

โœ” Integration Testing

โœ” Debugging Techniques

โœ” Performance Testing

๐Ÿš€ STEP 8: Build Industry-Level Projects

โœ” E-commerce Platform

โœ” Social Media App

โœ” Banking System

โœ” Project Management Tool

โœ” SaaS Application

๐Ÿ’ผ STEP 9: Interview Preparation

โœ” DSA Revision

โœ” System Design

โœ” Behavioral Interviews

โœ” Resume Building

โœ” GitHub Portfolio

๐ŸŽฏ STEP 10: Land Your First Job

โœ” Apply Strategically

โœ” Network on LinkedIn

โœ” Contribute to Open Source

โœ” Ace Technical Interviews

โœ” Negotiate Your Offer

๐Ÿ’ก Double Tap โค๏ธ For More
โค7
๐Ÿ“Š ๐—ช๐—ฎ๐—ป๐˜ ๐˜๐—ผ ๐—•๐—ฒ๐—ฐ๐—ผ๐—บ๐—ฒ ๐—ฎ ๐—ฃ๐—ฟ๐—ผ ๐—ถ๐—ป ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€? ๐Ÿš€

Learning Excel, SQL and Power BI is only the beginning. To stand out as a Data Analyst, focus on practical experience, visibility and networking.

๐Ÿ”ฅ 4 Ways to Level Up Your Data Analytics Career:

๐Ÿ’ก Master the Skills โ†’ Build Projects โ†’ Create Your Portfolio โ†’ Get Noticed

๐Ÿ”— ๐—–๐—ต๐—ฒ๐—ฐ๐—ธ ๐˜๐—ต๐—ฒ ๐—–๐—ผ๐—บ๐—ฝ๐—น๐—ฒ๐˜๐—ฒ ๐—š๐˜‚๐—ถ๐—ฑ๐—ฒ ๐Ÿ‘‡

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๐ŸŽฏ Perfect for Students | Freshers | Data Analyst Aspirants | Career Switchers
๐ŸŽ“ ๐Ÿฐ ๐—™๐—ฅ๐—˜๐—˜ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ฎ๐˜๐—ถ๐—ผ๐—ป๐˜€ ๐—ง๐—ผ ๐— ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ ๐—œ๐—ป ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฒ ๐Ÿš€

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๐Ÿ“Š ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ :- https://pdlink.in/4qn5q94

๐Ÿ’ซ ๐—”๐—œ & ๐— ๐—ฎ๐—ฐ๐—ต๐—ถ๐—ป๐—ฒ ๐—Ÿ๐—ฒ๐—ฎ๐—ฟ๐—ป๐—ถ๐—ป๐—ด :- https://pdlink.in/4zrkYNg

โ˜๏ธ ๐—–๐—น๐—ผ๐˜‚๐—ฑ ๐—–๐—ผ๐—บ๐—ฝ๐˜‚๐˜๐—ถ๐—ป๐—ด :- https://pdlink.in/4wzy6Ny

๐Ÿ›ก๏ธ ๐—–๐˜†๐—ฏ๐—ฒ๐—ฟ ๐—ฆ๐—ฒ๐—ฐ๐˜‚๐—ฟ๐—ถ๐˜๐˜† :- https://pdlink.in/4xMJNl5

๐Ÿ” ๐—ฆ๐—ต๐—ฎ๐—ฟ๐—ฒ this with your friends and classmates!
๐——๐—ฎ๐˜๐—ฎ ๐—ฆ๐—ฐ๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ ๐—™๐—ฅ๐—˜๐—˜ ๐—ข๐—ป๐—น๐—ถ๐—ป๐—ฒ ๐— ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ๐—ฐ๐—น๐—ฎ๐˜€๐˜€ ๐Ÿ˜

๐Ÿ’ซKickstart Your Data Science Career

๐Ÿ’ซJoin this Masterclass for an expert-led session on Data Science

Eligibility :- Students ,Freshers & Working Professionals

๐—ฅ๐—ฒ๐—ด๐—ถ๐˜€๐˜๐—ฒ๐—ฟ ๐—™๐—ผ๐—ฟ ๐—™๐—ฅ๐—˜๐—˜ ๐Ÿ‘‡:-

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(Only few slots left )

Date & Time :- 21st August 2026 & 7PM
โค1
๐—ช๐—ข๐—ฅ๐—ž ๐—™๐—ฅ๐—ข๐—  ๐—›๐—ข๐— ๐—˜ ๐—๐—ข๐—• ๐—ข๐—ฃ๐—ฃ๐—ข๐—ฅ๐—ง๐—จ๐—ก๐—œ๐—ง๐—ฌ ๐Ÿ˜

Company Name :- AI InsurTech Company

๐Ÿ’ผ ๐—ฅ๐—ผ๐—น๐—ฒ: Backend Developer
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๐Ÿ  ๐—ช๐—ผ๐—ฟ๐—ธ ๐— ๐—ผ๐—ฑ๐—ฒ: Work From Home
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๐ŸŽ“ ๐—ช๐—ต๐—ผ ๐—–๐—ฎ๐—ป ๐—”๐—ฝ๐—ฝ๐—น๐˜†?
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โšก Apply early and share this opportunity with your friends!
โค2
โ˜๏ธ ๐Ÿฐ ๐—™๐—ฅ๐—˜๐—˜ ๐—š๐—ผ๐—ผ๐—ด๐—น๐—ฒ ๐—–๐—น๐—ผ๐˜‚๐—ฑ ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ | ๐—•๐˜‚๐—ถ๐—น๐—ฑ ๐—œ๐—ป-๐——๐—ฒ๐—บ๐—ฎ๐—ป๐—ฑ ๐—–๐—น๐—ผ๐˜‚๐—ฑ ๐—ฆ๐—ธ๐—ถ๐—น๐—น๐˜€

Explore these Google Cloud learning resources covering cloud fundamentals, infrastructure, networking, security, data and AI/ML.

๐Ÿ”ฅ 4 Courses to Explore:
1๏ธโƒฃ Cloud Computing Fundamentals
2๏ธโƒฃ Infrastructure in Google Cloud
3๏ธโƒฃ Networking & Security in Google Cloud
4๏ธโƒฃ Data, ML & AI in Google Cloud

๐Ÿ”— ๐—˜๐—ป๐—ฟ๐—ผ๐—น๐—น ๐—™๐—ผ๐—ฟ ๐—™๐—ฅ๐—˜๐—˜๐Ÿ‘‡:- 

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๐ŸŽฏ Perfect for Students | Freshers | Developers | Cloud & DevOps Aspirants
โค1
๐Ÿš€ ๐—”๐—œ & ๐— ๐—ฎ๐—ฐ๐—ต๐—ถ๐—ป๐—ฒ ๐—Ÿ๐—ฒ๐—ฎ๐—ฟ๐—ป๐—ถ๐—ป๐—ด ๐—™๐—ฅ๐—˜๐—˜ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ

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https://pdlink.in/4zrkYNg

โšก Limited opportunityโ€”start learning today!
๐Ÿ’ป HOW TO DEBUG YOUR CODE ๐Ÿ›๐Ÿ”

1๏ธโƒฃ READ THE ERROR MESSAGE

Don't ignore the error.

An error message usually tells you:

๐Ÿ‘‰ What went wrong

๐Ÿ‘‰ Where it happened

๐Ÿ‘‰ Sometimes why it happened

Example:

"NameError: name 'total' is not defined"

This tells you that Python cannot find a variable called "total".

2๏ธโƒฃ CHECK THE LINE NUMBER

Most programming errors tell you where the problem occurred.

Go directly to that line.

Then check:

โ€ข Variable names

โ€ข Syntax

โ€ข Data types

โ€ข Function calls

โ€ข Missing brackets

โ€ข Incorrect indentation

3๏ธโƒฃ UNDERSTAND THE ERROR TYPE

Common errors beginners encounter:

"SyntaxError" โ†’ Code doesn't follow the language syntax.

"NameError" โ†’ You used a name that hasn't been defined.

"TypeError" โ†’ An operation was performed on an incompatible data type.

"IndexError" โ†’ You tried to access an invalid index.

"KeyError" โ†’ A dictionary key doesn't exist.

"ValueError" โ†’ A value has the wrong format or isn't acceptable.

๐Ÿ‘‰ Learn what common errors mean instead of simply searching for fixes.

4๏ธโƒฃ CHECK YOUR ASSUMPTIONS

Sometimes your code runs without an error but produces the wrong result.

Example:

"age = "25""

You might think "age" contains a number.

But it actually contains a string.

Always ask:

๐Ÿ‘‰ What type is this variable?

๐Ÿ‘‰ What value does it currently contain?

5๏ธโƒฃ PRINT INTERMEDIATE VALUES

When you're unsure what is happening, inspect your variables.

Example:

"print(total)"

"print(count)"

"print(average)"

This helps you understand how the values change while your program runs.

6๏ธโƒฃ BREAK THE PROBLEM INTO SMALL PARTS

Don't debug 200 lines of code at once.

Separate the problem.

Instead of asking:

โŒ "Why doesn't my program work?"

Ask:

โœ… "Is my input correct?"

Then:

โœ… "Is my calculation correct?"

Then:

โœ… "Is my loop working?"

Then:

โœ… "Is my output correct?"

Small questions are easier to solve.

7๏ธโƒฃ CHECK YOUR LOOP

Loops are a common source of bugs.

Check:

๐Ÿ‘‰ Where does the loop start?

๐Ÿ‘‰ When does it stop?

๐Ÿ‘‰ Is the condition correct?

๐Ÿ‘‰ Is the variable being updated?

๐Ÿ‘‰ Could this become an infinite loop?

Example:

"while count < 10:"

" print(count)"

" count += 1"

If "count" never changes, the loop may never end.

8๏ธโƒฃ CHECK YOUR DATA TYPES

Many bugs happen because developers expect one type but receive another.

Example:

""10" + "20""

Result:

""1020""

But:

10 + 20

Result:

30

The values look similar, but their data types are different.

9๏ธโƒฃ TEST WITH SIMPLE INPUT

If your program fails with complicated data, simplify it.

Instead of:

[15, 82, 43, 91, 27, 64, 10]

Try:

[1, 2, 3]

Then:

[1]

Then:

[]

Simple inputs make problems easier to identify.

๐Ÿ”Ÿ TEST EDGE CASES

Always test unusual situations.

Examples:

โ€ข Empty input

โ€ข One element

โ€ข Duplicate values

โ€ข Negative numbers

โ€ข Very large numbers

โ€ข Missing values

โ€ข Invalid input

A solution isn't truly reliable until you understand how it behaves in these situations.

1๏ธโƒฃ1๏ธโƒฃ USE A DEBUGGER

As your programs become larger, use debugging tools.

A debugger allows you to:

๐Ÿ”น Pause execution

๐Ÿ”น Inspect variables

๐Ÿ”น Execute code step by step

๐Ÿ”น Set breakpoints

๐Ÿ”น Find where the logic goes wrong

This is much more powerful than adding "print()" everywhere.
1๏ธโƒฃ2๏ธโƒฃ DON'T CHANGE EVERYTHING AT ONCE

Suppose your code has a bug.

Don't change five different things and run it again.

Instead:

๐Ÿ‘‰ Change one thing

๐Ÿ‘‰ Run the program

๐Ÿ‘‰ Observe the result

๐Ÿ‘‰ Understand what changed

This makes it much easier to identify the actual cause.

1๏ธโƒฃ3๏ธโƒฃ REPRODUCE THE BUG

Before fixing a problem, make sure you can consistently reproduce it.

Ask:

"When exactly does this error happen?"

For example:

โŒ It fails sometimes.

Better:

โœ… It fails when the input list is empty.

Now you have a specific problem to investigate.

1๏ธโƒฃ4๏ธโƒฃ FIX THE ROOT CAUSE

Don't just hide the error.

Example:

If a variable becomes "None" unexpectedly, don't simply add code that ignores "None".

Find out:

๐Ÿ‘‰ Why did it become "None"?

Fixing the root cause prevents the same problem from appearing elsewhere.

1๏ธโƒฃ5๏ธโƒฃ RETEST AFTER FIXING

Your job isn't finished when the error disappears.

Run:

โœ… The original test

โœ… Normal cases

โœ… Edge cases

โœ… Related functionality

A fix can sometimes create a new bug.

๐Ÿ”ฅ THE DEBUGGING FORMULA

Read the error

โ†“

Find the location

โ†“

Understand the error

โ†“

Check variables & data types

โ†“

Reproduce the problem

โ†“

Test with simple input

โ†“

Debug step by step

โ†“

Fix the root cause

โ†“

Test again

๐Ÿ’ก REMEMBER:

Every programmer writes buggy code.

The difference between a beginner and an experienced programmer isn't that experienced programmers never make mistakes.

They know how to find, understand, and fix them.

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