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
显示更多📈 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 位。
📊 受众指标与增长动态
自 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 天
+19430 天
帖子存档
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!👨💻
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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 :)
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GeeksForGeeks is a tool to learn
It doesn't matter:
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- 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:
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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
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𝟱 𝗙𝗿𝗲𝗲 𝗠𝗜𝗧 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗬𝗼𝘂 𝗖𝗮𝗻 𝗧𝗮𝗸𝗲 𝗢𝗻𝗹𝗶𝗻𝗲 — 𝗡𝗼 𝗟𝗼𝗴𝗶𝗻, 𝗡𝗼 𝗙𝗲𝗲𝘀!😍
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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
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📌 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 ❤️
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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.
现已上线!2025 年 Telegram 研究 — 年度关键洞察 
