Coding Interview Resources
52.3K subscribers
904 photos
7 files
590 links
This channel contains the free resources and solution of coding problems which are usually asked in the interviews.

Managed by: @love_data
Download Telegram
Python Interview Questions with Answers
โค1
๐Ÿš€ ๐—™๐—ฅ๐—˜๐—˜ ๐—™๐—ฟ๐—ฒ๐˜€๐—ต๐—ฒ๐—ฟ ๐—›๐—ถ๐—ฟ๐—ถ๐—ป๐—ด ๐——๐—ฟ๐—ถ๐˜ƒ๐—ฒ | ๐—ง๐—ฒ๐—ฐ๐—ต ๐—ฅ๐—ผ๐—น๐—ฒ๐˜€ ๐—จ๐—ฝ ๐˜๐—ผ โ‚น๐Ÿญ๐Ÿฎ ๐—Ÿ๐—ฃ๐—”!๐Ÿ”ฅ

Internship + Pre-Placement Offer

๐Ÿ’ผ Company: GoComet
๐Ÿ’ฐ Stipend: โ‚น30,000โ€“35,000/Month
๐Ÿš€ PPO: Up to โ‚น12 LPA

๐Ÿ“ Assessment Centres: Pune | Hyderabad | Noida | Chennai | Bangalore

๐Ÿ”— ๐—”๐—ฝ๐—ฝ๐—น๐˜† ๐—ก๐—ผ๐˜„ ๐Ÿ‘‡:

Full Stack Intern:- https://pdlink.in/4z3vF8o

AI First SDET Interns :- https://pdlink.in/4hS1Am2

โณ Limited Hiring Slots Available
โค1
๐Ÿš€ ๐—œ๐—•๐—  ๐—™๐—ฅ๐—˜๐—˜ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐ŸŽ“

Upgrade your tech skills with 100% FREE IBM certification courses and build a strong foundation in AI, Data Science, Cloud Computing, SQL, Python, and Machine Learning.

๐ŸŽฏ Perfect For
๐ŸŽ“ Students & Freshers
๐Ÿ‘จโ€๐Ÿ’ป Software Developers
๐Ÿ“Š Data Analysts
๐Ÿค– AI & Data Science Aspirants
๐Ÿ’ผ Working Professionals

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

https://pdlink.in/45KgqDR

๐Ÿ”ฅ Start learning today and prepare yourself for high-paying opportunities in the tech industry!
โค2๐Ÿ‘1
๐Ÿš€ ๐—ง๐—ผ๐—ฝ ๐—ฃ๐—ผ๐˜„๐—ฒ๐—ฟ ๐—•๐—œ ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฒ๐˜„ ๐—ค๐˜‚๐—ฒ๐˜€๐˜๐—ถ๐—ผ๐—ป๐˜€ ๐—”๐˜€๐—ธ๐—ฒ๐—ฑ ๐—ฏ๐˜† ๐—Ÿ๐—ฒ๐—ฎ๐—ฑ๐—ถ๐—ป๐—ด ๐—–๐—ผ๐—บ๐—ฝ๐—ฎ๐—ป๐—ถ๐—ฒ๐˜€ ๐Ÿ“Š

๐Ÿ’ผ Companies hiring Power BI professionals include: Microsoft, Deloitte, Accenture, Capgemini, TCS, Infosys, Cognizant, EY, PwC, KPMG, IBM, Wipro, and many more.

โœ… Frequently Asked Interview Questions
โœ… Beginner to Advanced Level Coverage
โœ… Improve Your Problem-Solving Skills
โœ… Build Interview Confidence
โœ… Prepare for Top MNC Hiring Drives

๐‹๐ข๐ง๐ค๐Ÿ‘‡:-

https://pdlink.in/4xqxg6v

๐Ÿ”ฅ Master Power BI interview concepts and take one step closer to landing your dream Data Analytics job!
โค1
๐Ÿš€ Complete SQL Roadmap ๐Ÿ—„๐Ÿ”ฅ

๐Ÿง  STEP 1: Learn SQL Basics
โœ” What is SQL?
โœ” Databases & Tables
โœ” SELECT Statement
โœ” WHERE Clause
โœ” ORDER BY

๐Ÿ›  Databases to Practice:
โœ” MySQL
โœ” PostgreSQL
โœ” SQL Server

๐Ÿ“Š STEP 2: Learn Filtering & Aggregation
โœ” DISTINCT
โœ” LIMIT & TOP
โœ” COUNT, SUM, AVG
โœ” MIN & MAX
โœ” GROUP BY & HAVING

โšก STEP 3: Master SQL JOINS
โœ” INNER JOIN
โœ” LEFT JOIN
โœ” RIGHT JOIN
โœ” FULL JOIN
โœ” SELF JOIN

๐Ÿ›  Concepts to Learn:
โœ” Primary Key
โœ” Foreign Key
โœ” Relationships

๐Ÿ“ˆ STEP 4: Learn Advanced SQL
โœ” Subqueries
โœ” Common Table Expressions (CTEs)
โœ” CASE WHEN
โœ” UNION & UNION ALL
โœ” EXISTS & IN

๐Ÿ”ฅ STEP 5: Learn Window Functions
โœ” ROW_NUMBER()
โœ” RANK()
โœ” DENSE_RANK()
โœ” LEAD() & LAG()
โœ” PARTITION BY

๐Ÿง  STEP 6: Learn Database Design
โœ” Normalization
โœ” Schema Design
โœ” Indexing
โœ” Constraints
โœ” Data Integrity

โ˜๏ธ STEP 7: Learn SQL Optimization
โœ” Query Optimization
โœ” Execution Plans
โœ” Index Optimization
โœ” Performance Tuning

๐Ÿ›  Tools to Learn:
โœ” DBeaver
โœ” pgAdmin
โœ” MySQL Workbench

๐Ÿ“‚ STEP 8: Build Real SQL Projects
โœ” Sales Database Analysis
โœ” Employee Management System
โœ” E-commerce Database
โœ” Customer Analytics
โœ” Inventory Management

๐Ÿ’ก SQL Notes: https://whatsapp.com/channel/0029VbCyzS02ZjCwoShXXc2j

๐Ÿ’ฌ Tap โค๏ธ if this helped you!
โค4
๐—™๐—ฅ๐—˜๐—˜ ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ & ๐——๐—ฎ๐˜๐—ฎ ๐—ฆ๐—ฐ๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐Ÿ“Š

Start learning with FREE courses from leading companies and build in-demand skills for 2026.

๐Ÿ”น Data Analytics Essentials โ€” Cisco
๐Ÿ”น Introduction to Data Science โ€” Cisco
๐Ÿ”น Python for Data Science โ€” IBM
๐Ÿ”น Azure Data Fundamentals โ€” Microsoft
๐Ÿ”น Google Analytics โ€” Google

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

https://pdlink.in/45QpA1I

๐Ÿ”ฅ Start learning today and upgrade your resume with job-ready Data & Analytics skills!
๐Ÿš€ Top Coding Interview Concepts โ€“ Part 4 ๐Ÿ’ป๐Ÿ”ฅ

31. Polymorphism

The ability of the same method or interface to behave differently depending on the object using it.

Example: Different classes can implement the same draw() method in different ways.

32. Abstraction

Hiding unnecessary implementation details and exposing only the essential functionality.

Example: You use a print() function without needing to know how the printer works internally.

33. Constructor

A special method that is automatically called when an object is created and is typically used to initialize its properties.

Example: A Car constructor can set the car's model and color when the object is created.

34. Interface

A contract that defines methods or behaviors a class must provide, without necessarily defining how they are implemented.

Example: A Payment interface may require pay() to be implemented by different payment methods.

35. Method Overloading

Defining multiple methods with the same name but different parameters.

Example: An add() method can accept two numbers or three numbers, depending on the language's support for overloading.

36. Method Overriding

When a child class provides its own implementation of a method already defined in its parent class.

Example: Dog can override an Animal class's sound() method.

37. Pointer

A variable that stores the memory address of another variable or object.

Example: Pointers are commonly used in C and C++ for direct memory manipulation.

38. Reference

A way to refer to an existing object or value without necessarily creating a separate copy of it.

Example: Multiple variables can reference the same object in memory.

39. Memory Management

The process of allocating, using, and releasing memory efficiently during program execution.

Example: Garbage collection automatically removes objects that are no longer needed in languages such as Java and Python.

40. Garbage Collection

An automatic memory-management process that identifies and frees memory occupied by objects that are no longer reachable or needed.

๐Ÿ’ฌ Double Tap โค๏ธ for Part 5!
โค1
๐Ÿš€ ๐— ๐—ถ๐—ฐ๐—ฟ๐—ผ๐˜€๐—ผ๐—ณ๐˜ ๐—™๐—ฅ๐—˜๐—˜ 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—ฒ๐˜€ ๐Ÿ“Š๐Ÿ”ฅ

Build in-demand Data Analytics skills with Microsoft and strengthen your resume with FREE learning opportunities.

โœ… Beginner-Friendly
โœ… Learn at Your Own Pace
โœ… Build Job-Ready Data Skills
โœ… Improve Your Resume & LinkedIn Profile
โœ… Prepare for Data Analyst & BI Careers

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

https://pdlink.in/4hXL4Ru

๐Ÿ”ฅ Start learning today and take your first step toward a career in Data Analytics & Business Intelligence
โค1
๐Ÿš€ ๐—™๐—ฅ๐—˜๐—˜ ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฒ๐˜„ ๐—ฅ๐—ฒ๐˜€๐—ผ๐˜‚๐—ฟ๐—ฐ๐—ฒ๐˜€ ๐—ฏ๐˜† ๐—ง๐—ผ๐—ฝ ๐—–๐—ผ๐—บ๐—ฝ๐—ฎ๐—ป๐—ถ๐—ฒ๐˜€๐Ÿ”ฅ

Get FREE access to company-specific interview kits, previous questions, preparation strategies, and important resources! ๐Ÿ‘‡

Google :- https://pdlink.in/4xtUyIG

Amazon :- https://pdlink.in/45Q0YWR

Microsoft :- https://pdlink.in/3Up1bha

Wipro :- https://pdlink.in/4fMo1rA

Infosys :- https://pdlink.in/3TRn8p0

๐Ÿ“Œ share it with friends preparing for placements
If you want to get a job as a machine learning engineer, donโ€™t start by diving into the hottest libraries like PyTorch,TensorFlow, Langchain, etc.

Yes, you might hear a lot about them or some other trending technology of the year...but guess what!

Technologies evolve rapidly, especially in the age of AI, but core concepts are always seen as more valuable than expertise in any particular tool. Stop trying to perform a brain surgery without knowing anything about human anatomy.

Instead, here are basic skills that will get you further than mastering any framework:


๐Œ๐š๐ญ๐ก๐ž๐ฆ๐š๐ญ๐ข๐œ๐ฌ ๐š๐ง๐ ๐’๐ญ๐š๐ญ๐ข๐ฌ๐ญ๐ข๐œ๐ฌ - My first exposure to probability and statistics was in college, and it felt abstract at the time, but these concepts are the backbone of ML.

You can start here: Khan Academy Statistics and Probability - https://www.khanacademy.org/math/statistics-probability

๐‹๐ข๐ง๐ž๐š๐ซ ๐€๐ฅ๐ ๐ž๐›๐ซ๐š ๐š๐ง๐ ๐‚๐š๐ฅ๐œ๐ฎ๐ฅ๐ฎ๐ฌ - Concepts like matrices, vectors, eigenvalues, and derivatives are fundamental to understanding how ml algorithms work. These are used in everything from simple regression to deep learning.

๐๐ซ๐จ๐ ๐ซ๐š๐ฆ๐ฆ๐ข๐ง๐  - Should you learn Python, Rust, R, Julia, JavaScript, etc.? The best advice is to pick the language that is most frequently used for the type of work you want to do. I started with Python due to its simplicity and extensive library support, and it remains my go-to language for machine learning tasks.

You can start here: Automate the Boring Stuff with Python - https://automatetheboringstuff.com/

๐€๐ฅ๐ ๐จ๐ซ๐ข๐ญ๐ก๐ฆ ๐”๐ง๐๐ž๐ซ๐ฌ๐ญ๐š๐ง๐๐ข๐ง๐  - Understand the fundamental algorithms before jumping to deep learning. This includes linear regression, decision trees, SVMs, and clustering algorithms.

๐ƒ๐ž๐ฉ๐ฅ๐จ๐ฒ๐ฆ๐ž๐ง๐ญ ๐š๐ง๐ ๐๐ซ๐จ๐๐ฎ๐œ๐ญ๐ข๐จ๐ง:
Knowing how to take a model from development to production is invaluable. This includes understanding APIs, model optimization, and monitoring. Tools like Docker and Flask are often used in this process.

๐‚๐ฅ๐จ๐ฎ๐ ๐‚๐จ๐ฆ๐ฉ๐ฎ๐ญ๐ข๐ง๐  ๐š๐ง๐ ๐๐ข๐  ๐ƒ๐š๐ญ๐š:
Familiarity with cloud platforms (AWS, Google Cloud, Azure) and big data tools (Spark) is increasingly important as datasets grow larger. These skills help you manage and process large-scale data efficiently.

You can start here: Google Cloud Machine Learning - https://cloud.google.com/learn/training/machinelearning-ai

I love frameworks and libraries, and they can make anyone's job easier.

But the more solid your foundation, the easier it will be to pick up any new technologies and actually validate whether they solve your problems.

Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624

All the best ๐Ÿ‘๐Ÿ‘
โค1
๐Ÿš€ ๐—š๐—ผ๐—ผ๐—ด๐—น๐—ฒ ๐—™๐—ฅ๐—˜๐—˜ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฒ ๐ŸŽ“

Want to upgrade your resume with Google skills and certifications Explore FREE learning opportunities and build in-demand skills for today's job market.

๐Ÿ‘‰Artificial Intelligence & Generative AI
๐Ÿ“Š Data Analytics
โ˜๏ธ Cloud Computing
๐Ÿ“ข Digital Marketing
๐Ÿ” Cybersecurity
๐Ÿ’ป Tech & Career Skills

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

https://pdlink.in/4z9pdgf

๐Ÿ”ฅ Don't just collect certificates โ€” build skills that can help you stand out in 2026!
๐Ÿš€ Top Coding Interview Concepts โ€“ Part 5 ๐Ÿ’ป๐Ÿ”ฅ

41. API โ†’ A set of rules and protocols that allows different software applications to communicate with each other.

42. REST API โ†’ An API architecture that uses HTTP methods and resources to enable communication between client and server.

43. HTTP Methods โ†’ Actions used to interact with resources through HTTP.

Example: GET โ†’ retrieve data, POST โ†’ create data, PUT โ†’ update data, DELETE โ†’ remove data.

44. JSON โ†’ A lightweight text-based format commonly used to exchange structured data between applications.

Example: {"name": "John", "age": 25}

45. Authentication โ†’ The process of verifying who a user or system is.

Example: Logging in with a username and password.

46. Authorization โ†’ The process of determining what an authenticated user is allowed to access or do.

Example: An admin can delete users, while a regular user cannot.

47. JWT (JSON Web Token) โ†’ A compact token format commonly used to securely transmit claims between systems and authenticate API requests.

48. Session โ†’ Information maintained by a server or application to keep track of a user's interaction over a period of time.

Example: Staying logged in while navigating between pages.

49. Cookie โ†’ A small piece of data stored by a browser and sent with requests to help websites remember information about a user or session.

50. Cache โ†’ Temporary storage used to keep frequently accessed data so it can be retrieved faster.

Example: A browser caches images so they load faster when you revisit a website.

๐Ÿ’ฌ Double Tap โค๏ธ for Part 6!
โค3