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Coding Interview Resources

Coding Interview Resources

前往频道在 Telegram

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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📈 Telegram 频道 Coding Interview Resources 的分析概览

频道 Coding Interview Resources (@crackingthecodinginterview) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 52 120 名订阅者,在 技术与应用 类别中位列第 2 563,并在 印度 地区排名第 7 263

📊 受众指标与增长动态

невідомо 创建以来,项目保持高速增长,吸引了 52 120 名订阅者。

根据 05 六月, 2026 的最新数据,频道保持稳定运转。过去 30 天订阅人数变化为 194,过去 24 小时变化为 11,整体触达仍然可观。

  • 认证状态: 未认证
  • 互动率 (ER): 平均受众互动率为 1.93%。内容发布后 24 小时内通常能获得 0.84% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 1 005 次浏览,首日通常累积 437 次浏览。
  • 互动与反馈: 受众积极参与,单帖平均反应数为 2
  • 主题关注点: 内容集中在 array, stack, algorithm, programming, sort 等核心主题上。

📝 描述与内容策略

作者将该频道定位为表达主观观点的平台:
This channel contains the free resources and solution of coding problems which are usually asked in the interviews. Managed by: @love_data

凭借高频更新(最新数据采集于 07 六月, 2026),频道始终保持新鲜度与高覆盖。分析显示受众积极互动,使其成为 技术与应用 类别中的关键影响点。

52 120
订阅者
+1124 小时
+407
+19430
帖子存档
𝗙𝗥𝗘𝗘 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝗧𝗼 𝗖𝗿𝗮𝗰𝗸 𝗬𝗼𝘂𝗿 𝗡𝗲𝘅𝘁 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 😍 Preparing for coding interviews? These fr
𝗙𝗥𝗘𝗘 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝗧𝗼 𝗖𝗿𝗮𝗰𝗸 𝗬𝗼𝘂𝗿 𝗡𝗲𝘅𝘁 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 😍 Preparing for coding interviews? These free resources will help you crack your dream job! 📌 Ace Your Next Interview with These FREE Resources!👨‍💻 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/3FjrIVX All The Best 🎊

SQL can be simple—if you learn it the smart way.. If you’re aiming to become a data analyst, mastering SQL is non-negotiable. Here’s a smart roadmap to ace it: 1. Basics First: Understand data types, simple queries (SELECT, FROM, WHERE). Master basic filtering. 2. Joins & Relationships: Dive into INNER, LEFT, RIGHT joins. Practice combining tables to extract meaningful insights. 3. Aggregations & Functions: Get comfortable with COUNT, SUM, AVG, MAX, GROUP BY, and HAVING clauses. These are essential for summarizing data. 4. Subqueries & Nested Queries: Learn how to query within queries. This is powerful for handling complex datasets. 5. Window Functions: Explore ranking, cumulative sums, and sliding windows to work with running totals and moving averages. 6. Optimization: Study indexing and query optimization for faster, more efficient queries. 7. Real-World Scenarios: Apply your SQL knowledge to solve real-world business problems. The journey may seem tough, but each step sharpens your skills and brings you closer to data analysis excellence. Stay consistent, practice regularly, and let SQL become your superpower! 💪 Here you can find essential SQL Interview Resources👇 https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v Like this post if you need more 👍❤️ Hope it helps :)

𝗧𝗼𝗽 𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗟𝗶𝗸𝗲 𝗜𝗻𝗳𝗼𝘀𝘆𝘀 , 𝗚𝗲𝗻𝗽𝗮𝗰𝘁 ,𝗟&𝗧 ,𝗣𝗵𝗶𝗹𝗶𝗽𝘀 & 𝗢𝗿𝗮𝗰𝗹𝗲 𝗛𝗶𝗿𝗶𝗻𝗴 😍 Role
𝗧𝗼𝗽 𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗟𝗶𝗸𝗲 𝗜𝗻𝗳𝗼𝘀𝘆𝘀 , 𝗚𝗲𝗻𝗽𝗮𝗰𝘁 ,𝗟&𝗧 ,𝗣𝗵𝗶𝗹𝗶𝗽𝘀 & 𝗢𝗿𝗮𝗰𝗹𝗲 𝗛𝗶𝗿𝗶𝗻𝗴 😍 Roles Hiring:- Data Analyst, Software Engineer & Associate Job Location:- Across India/WFH  Qualification:- Graduate/Post Graduate  𝗔𝗽𝗽𝗹𝘆 𝗡𝗼𝘄👇:- https://bit.ly/44qMX2k Select your experience & Complete The Registration Process  Select the company name & apply for the role that matches you

💡 Must Have Tools for Programmers
+7
💡 Must Have Tools for Programmers

𝟲 𝗙𝗿𝗲𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘁𝗼 𝗦𝘁𝗮𝗿𝘁 𝗬𝗼𝘂𝗿 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 & 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗝𝗼𝘂𝗿𝗻𝗲𝘆😍 Want to bre
𝟲 𝗙𝗿𝗲𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘁𝗼 𝗦𝘁𝗮𝗿𝘁 𝗬𝗼𝘂𝗿 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 & 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗝𝗼𝘂𝗿𝗻𝗲𝘆😍 Want to break into Data Science & Analytics but don’t want to spend on expensive courses?👨‍💻 Start here — with 100% FREE courses from Cisco, IBM, Google & LinkedIn, all with certificates you can showcase on LinkedIn or your resume!📚📌 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/3Ix2oxd This list will set you up with real-world, job-ready skills✅️

Leetcode is a tool to learn Neetcode is a tool to learn CodeChef is a tool to learn Codeforces is a tool to learn HackerRank is a tool to learn GeeksForGeeks is a tool to learn It doesn't matter: - which platform you are using - or how many problems you solve All that matters is how strong you grasp concepts and adapt to problems. Don't chase the status of 500 or 1000 problems solved. Chase proper learning & training your mind for problem-solving. Best DSA RESOURCES: https://topmate.io/coding/886874 All the best 👍👍

Learning DSA wasn’t just about acing interviews, --- it was about thinking better, building faster, and debugging smarter. 🎯 𝗛𝗲𝗿𝗲 𝗮𝗿𝗲 𝘁𝗵𝗲 𝟵 𝗰𝗼𝗿𝗲 𝗽𝗮𝘁𝘁𝗲𝗿𝗻𝘀 𝘁𝗵𝗮𝘁 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗲𝗱 𝗵𝗼𝘄 𝗜 𝘀𝗼𝗹𝘃𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺𝘀: • Sliding Windows • Two Pointers • Stack Based Patterns • Dynamic Programing • BFS/DFS (Trees & Graphs) • Merge Intervals • Backtracking & Subsets • top-k Elements (Heaps) • Greedy Techniques 🛤️ 𝗠𝘆 𝗣𝗮𝘁𝗵 𝘁𝗼 𝗠𝗮𝘀𝘁𝗲𝗿𝗶𝗻𝗴 𝗗𝗦𝗔: • Started with basic problems on arrays & strings • Solved 1-2 problems a day, consistently for 3 months • Focused more on patterns than individual questions • Made my own notes, revisited problems I struggled with • Used visual tools to understand recursion & DP • Practiced explaining my solutions out loud (like system design reviews) • Applied patterns in real-world projects (DevOps automation, log parsing, infra tools) 💡 𝗟𝗼𝗼𝗸𝗶𝗻𝗴 𝗯𝗮𝗰𝗸, 𝗼𝗻𝗲 𝘁𝗵𝗶𝗻𝗴 𝗶𝘀 𝗰𝗹𝗲𝗮𝗿: > It's not how many problems you solve, it's how well you can recognize the pattern hiding in each one. You can find more free resources on my WhatsApp channel: https://whatsapp.com/channel/0029VahiFZQ4o7qN54LTzB17

🚀 THE 7-DAY PROFIT CHALLENGE! 🚀 Can you turn $100 into $5,000 in just 7 days? Jay can. And she’s challenging YOU to do the
🚀 THE 7-DAY PROFIT CHALLENGE! 🚀 Can you turn $100 into $5,000 in just 7 days? Jay can. And she’s challenging YOU to do the same. 👇 https://t.me/+mVE5EOYsAycxNTE1 https://t.me/+mVE5EOYsAycxNTE1 https://t.me/+mVE5EOYsAycxNTE1

Data Science Roadmap: 🗺 📂 Math & Stats  ∟📂 Python/R   ∟📂 Data Wrangling    ∟📂 Visualization     ∟📂 ML      ∟📂 DL & NLP       ∟📂 Projects        ∟ ✅ Apply For Job Like if you need detailed explanation step-by-step ❤️

Roadmap to become Data Scientist
Roadmap to become Data Scientist

I was lost in crypto noise — until I found a channel that shows where the real money is made👍 No hype, just clear signals an
I was lost in crypto noise — until I found a channel that shows where the real money is made👍 No hype, just clear signals and smart entries. 👉🏼 Subscribe now — all you need to do is follow the trades. It’s that simple: https://t.me/+ixExN-YdZsc5M2Iy

SQL Interview Questions with Answers 1. How to change a table name in SQL? This is the command to change a table name in SQL: ALTER TABLE table_name RENAME TO new_table_name; We will start off by giving the keywords ALTER TABLE, then we will follow it up by giving the original name of the table, after that, we will give in the keywords RENAME TO and finally, we will give the new table name. 2. How to use LIKE in SQL? The LIKE operator checks if an attribute value matches a given string pattern. Here is an example of LIKE operator SELECT * FROM employees WHERE first_name like ‘Steven’; With this command, we will be able to extract all the records where the first name is like “Steven”. 3. If we drop a table, does it also drop related objects like constraints, indexes, columns, default, views and sorted procedures? Yes, SQL server drops all related objects, which exists inside a table like constraints, indexes, columns, defaults etc. But dropping a table will not drop views and sorted procedures as they exist outside the table. 4. Explain SQL Constraints. SQL Constraints are used to specify the rules of data type in a table. They can be specified while creating and altering the table. The following are the constraints in SQL: NOT NULL CHECK DEFAULT UNIQUE PRIMARY KEY FOREIGN KEY React ❤️ for more

𝟱 𝗙𝗿𝗲𝗲 𝗠𝗜𝗧 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗬𝗼𝘂 𝗖𝗮𝗻 𝗧𝗮𝗸𝗲 𝗢𝗻𝗹𝗶𝗻𝗲 — 𝗡𝗼 𝗟𝗼𝗴𝗶𝗻, 𝗡𝗼 𝗙𝗲𝗲𝘀!😍 Dream of learning f
𝟱 𝗙𝗿𝗲𝗲 𝗠𝗜𝗧 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗬𝗼𝘂 𝗖𝗮𝗻 𝗧𝗮𝗸𝗲 𝗢𝗻𝗹𝗶𝗻𝗲 — 𝗡𝗼 𝗟𝗼𝗴𝗶𝗻, 𝗡𝗼 𝗙𝗲𝗲𝘀!😍 Dream of learning from MIT without spending a rupee? 👨‍🎓 These free online courses from Massachusetts Institute of Technology cover some of the most in-demand topics 📚📌 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/4lLMflG Now’s your chance. 💡

📌 Python Cheatsheet: Master the Foundations & Beyond Start learning Python → ⬇️ Core Python Building Blocks Basic Commands → print() – Display output → input() – Get user input → len() – Get length of a data structure → type() – Get variable type → range() – Generate a sequence → help() – Get documentation Data Types → int, float, bool, str – Numbers & text → list, tuple, dict, set – Data collections Control Structures → if / elif / else – Conditional logic → for, while – Loops → break, continue, pass – Loop control ⬇️ Advanced Concepts Functions & Classes → def, return, lambda – Define functions → class, init, self – Object-oriented programming Modules → import, from ... import – Reuse code ⬇️ Special Tools Exception Handling → try, except, finally, raise – Handle errors File Handling → open(), read(), write(), close() – Manage files Decorators & Generators → @decorator, yield – Extend or pause functions List Comprehension → [x for x in list if condition] – Create lists efficiently Like for more ❤️

🔥𝗙𝗿𝗲𝗲 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 – 𝗘𝗻𝗿𝗼𝗹𝗹 𝗕𝗲𝗳𝗼𝗿𝗲 𝗜𝘁 𝗘𝗻𝗱𝘀! Get certified in
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⌨️ Hide secret message in image using Python
⌨️ Hide secret message in image using Python

📌 Python Cheatsheet: Master the Foundations & Beyond Start learning Python → ⬇️ Core Python Building Blocks Basic Commands → print() – Display output → input() – Get user input → len() – Get length of a data structure → type() – Get variable type → range() – Generate a sequence → help() – Get documentation Data Types → int, float, bool, str – Numbers & text → list, tuple, dict, set – Data collections Control Structures → if / elif / else – Conditional logic → for, while – Loops → break, continue, pass – Loop control ⬇️ Advanced Concepts Functions & Classes → def, return, lambda – Define functions → class, init, self – Object-oriented programming Modules → import, from ... import – Reuse code ⬇️ Special Tools Exception Handling → try, except, finally, raise – Handle errors File Handling → open(), read(), write(), close() – Manage files Decorators & Generators → @decorator, yield – Extend or pause functions List Comprehension → [x for x in list if condition] – Create lists efficiently Like for more ❤️

𝟯 𝗙𝗥𝗘𝗘 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘁𝗼 𝗦𝘁𝗮𝗿𝘁 𝗬𝗼𝘂𝗿 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗖𝗮𝗿𝗲𝗲𝗿 𝗶𝗻 𝟮𝟬𝟮𝟱!😍 Want to break i
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What is Docker ? 1 • Development Lets say You created an Application And that's working fine in your machine 2 • Production But in Production it doesn't work properly Developers experince it a lot 3 • That is when the Developer's famous words are spoken Client - Your application is not working 😡 Developer - It's working on my Machine 😒 4 • The Reason could be due to: • Dependencies • Libraries and versions • Framework • OS Level features • Microservices That the developers machine has but not there in the production environment 5 • DOCKER We need a standardized way to package the application with its dependencies and deploy it on any environment. Docker is a tool designed to make it easier to create, deploy, and run applications by using containers. So it will always work the same regardless of its environment 6 • How Does Docker Work? Docker packages an application and all its dependencies in a virtual container that can run on any Linux server. 7 • Each container runs as an isolated process in the user space and take up less space than regular VMs due to their layered architecture.

Coding Interview Resources - Telegram 频道 @crackingthecodinginterview 的统计与分析