Artificial Intelligence & ChatGPT Prompts
🔓Unlock Your Coding Potential with ChatGPT 🚀 Your Ultimate Guide to Ace Coding Interviews! 💻 Coding tips, practice questions, and expert advice to land your dream tech job. For Promotions: @love_data
显示更多📈 Telegram 频道 Artificial Intelligence & ChatGPT Prompts 的分析概览
频道 Artificial Intelligence & ChatGPT Prompts (@curiousprogrammer) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 42 100 名订阅者,在 技术与应用 类别中位列第 3 208,并在 印度 地区排名第 9 253 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 42 100 名订阅者。
根据 23 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 129,过去 24 小时变化为 -20,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 1.84%。内容发布后 24 小时内通常能获得 0.43% 的反应,占订阅者总量。
- 帖子覆盖: 每篇帖子平均可获得 775 次浏览,首日通常累积 183 次浏览。
- 互动与反馈: 受众积极参与,单帖平均反应数为 3。
- 主题关注点: 内容集中在 learning, algorithm, detection, llm, pattern 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:
“🔓Unlock Your Coding Potential with ChatGPT
🚀 Your Ultimate Guide to Ace Coding Interviews!
💻 Coding tips, practice questions, and expert advice to land your dream tech job.
For Promotions: @love_data”
凭借高频更新(最新数据采集于 24 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。
数据加载中...
| 日期 | 订阅者增长 | 提及 | 频道 | |
| 23 六月 | +5 | |||
| 22 六月 | 0 | |||
| 21 六月 | 0 | |||
| 20 六月 | 0 | |||
| 19 六月 | +9 | |||
| 18 六月 | +1 | |||
| 17 六月 | +2 | |||
| 16 六月 | +8 | |||
| 15 六月 | +8 | |||
| 14 六月 | +13 | |||
| 13 六月 | +20 | |||
| 12 六月 | +13 | |||
| 11 六月 | +1 | |||
| 10 六月 | +9 | |||
| 09 六月 | +7 | |||
| 08 六月 | +7 | |||
| 07 六月 | +10 | |||
| 06 六月 | +4 | |||
| 05 六月 | +23 | |||
| 04 六月 | +7 | |||
| 03 六月 | +13 | |||
| 02 六月 | +17 | |||
| 01 六月 | +3 |
| 2 | 🔰 Anonymous function in Python. | 347 |
| 3 | 𝗣𝗮𝘆 𝗔𝗳𝘁𝗲𝗿 𝗣𝗹𝗮𝗰𝗲𝗺𝗲𝗻𝘁 - 𝗙𝘂𝗹𝗹𝘀𝘁𝗮𝗰𝗸𝗗𝗲𝘃 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗪𝗶𝘁𝗵 𝗚𝗲𝗻𝗔𝗜 😍
Curriculum designed and taught by alumni from IITs & leading tech companies.
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| 4 | How to send follow up email to a recruiter 👇👇
Dear [Recruiter’s Name],
I hope this email finds you doing well. I wanted to take a moment to express my sincere gratitude for the time and consideration you have given me throughout the recruitment process for the [position] role at [company].
I understand that you must be extremely busy and receive countless applications, so I wanted to reach out and follow up on the status of my application. If it’s not too much trouble, could you kindly provide me with any updates or feedback you may have?
I want to assure you that I remain genuinely interested in the opportunity to join the team at [company] and I would be honored to discuss my qualifications further. If there are any additional materials or information you require from me, please don’t hesitate to let me know.
Thank you for your time and consideration. I appreciate the effort you put into recruiting and look forward to hearing from you soon.
Warmest regards,
(Tap to copy) | 384 |
| 5 | 𝗔𝗰𝗰𝗲𝗻𝘁𝘂𝗿𝗲 𝗙𝗥𝗘𝗘 𝗩𝗶𝗿𝘁𝘂𝗮𝗹 𝗜𝗻𝘁𝗲𝗿𝗻𝘀𝗵𝗶𝗽 𝗳𝗼𝗿 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝘄𝗶𝘁𝗵 𝗙𝗿𝗲𝗲 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗲 📊
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| 6 | 🔹 Placement Ready in 3 Months! 🔹
1. Month 1: Aptitude
- Quantitative Aptitude, Logical Reasoning, Verbal Ability
- Daily practice and mock tests
2. Month 1 & 2: Course Fundamentals
- OOPS, DBMS, OS, CN, Java, C++
- Study plan and resources
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- Data Structures and Algorithms (DSA)
- Practice on platforms like Hackerrank, Codechef, and Leetcode
4. Projects, Skills, and Internships
- Full-stack or ML projects
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5. Month 3: Mock Interviews
- Practice with Pramp and peers
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All the best 👍👍 | 324 |
| 7 | 🚀 𝗧𝗼𝗽 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝗬𝗼𝘂 𝗖𝗮𝗻 𝗟𝗲𝗮𝗿𝗻 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘! 💼🔥
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| 8 | On Reddit, someone collected all the resources they used to prepare for interviews on algorithms, system design, and machine coding. In the end, they made it to a Google interview.
1. Algorithms and Patterns
Before grinding on problems, it's worth understanding the patterns.
• All LeetCode Articles on Coding Patterns Summarized
https://leetcode.com/discuss/interview-question/5366542/all-leetcode-articles-on-coding-patterns-summarized-in-one-page
• Solved All Two Pointers Problems in 100 Days
https://leetcode.com/discuss/study-guide/1688903/Solved-all-two-pointers-problems-in-100-days
• Tree Question Pattern 2023 — Tree Study Guide
https://leetcode.com/discuss/study-guide/2879240/tree-question-pattern-2023-tree-study-guide
• Important and Useful Links from All Over LeetCode
https://leetcode.com/discuss/general-discussion/665604/Important-and-Useful-links-from-all-over-the-LeetCode
• Coding Interview Preparation Problems for Beginners
https://leetcode.com/discuss/interview-question/448284/Coding-Interview-preparation-problems-for-beginners
2. Preparation for Companies
• Google, Meta, Apple, Amazon Senior SDE Preparation
https://prachub.com/?sort=hot&company=Meta%2CGoogle%2CTikTok%2CAmazon
• A Study Guide for Passing the Google Interview
https://prachub.com/interview-guide
The author also made a small tracker for preparation:
• company-specific questions
• Todo / Solved / Revision statuses
• automatic repetition scheduling
• AI assistant with hints instead of ready-made solutions
https://prachub.com/questions
3. System Design (HLD)
Instead of random articles — structured collections:
• Arch 25 — the most common systems and patterns
• Arch 50 — infrastructure, data, and fault tolerance
• Arch 75 — more complex scenarios and company-specific specialization
• Arch All — a full bank of 103 HLD tasks
• Core Concepts — 33 breakdowns of distributed systems
4. Machine Coding / LLD
Many underestimate this part until their first interview failure.
• MaCo 30 — the most common tasks
• MaCo 60 — an extended collection
• MaCo All — a full set of 103 tasks
• Design Patterns — 31 design patterns | 350 |
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| 10 | AI/ML roadmap
Topic: Mathematics
- Subtopic: Linear Algebra
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- Subtopic: Calculus
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- Subtopic: Probability and Statistics
- Probability Theory, Random Variables, Statistical Inference
Topic: Programming
- Subtopic: Python
- Python Basics, Libraries like NumPy, Pandas, Matplotlib
Topic: Machine Learning
- Subtopic: Supervised Learning
- Linear Regression, Logistic Regression, Decision Trees
- Subtopic: Unsupervised Learning
- Clustering, Dimensionality Reduction[1](https://i.am.ai/roadmap)
- Subtopic: Neural Networks and Deep Learning
- Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks
Topic: Specializations
- Subtopic: Natural Language Processing
- Text Preprocessing, Topic Modeling, Word Embeddings
- Subtopic: Computer Vision
- Image Processing, Object Detection, Image Segmentation
- Subtopic: Reinforcement Learning
- Markov Decision Processes, Q-Learning, Policy Gradients
Join for more: https://t.me/machinelearning_deeplearning | 392 |
| 11 | 📊 𝗖𝗶𝘀𝗰𝗼 𝗙𝗥𝗘𝗘 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 | 𝗘𝗻𝗿𝗼𝗹𝗹 𝗡𝗼𝘄! 🚀
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| 12 | Most Asked SQL Interview Questions at MAANG Companies🔥🔥
Preparing for an SQL Interview at MAANG Companies? Here are some crucial SQL Questions you should be ready to tackle:
1. How do you retrieve all columns from a table?
SELECT * FROM table_name;
2. What SQL statement is used to filter records?
SELECT * FROM table_name
WHERE condition;
The WHERE clause is used to filter records based on a specified condition.
3. How can you join multiple tables? Describe different types of JOINs.
SELECT columns
FROM table1
JOIN table2 ON table1.column = table2.column
JOIN table3 ON table2.column = table3.column;
Types of JOINs:
1. INNER JOIN: Returns records with matching values in both tables
SELECT * FROM table1
INNER JOIN table2 ON table1.column = table2.column;
2. LEFT JOIN: Returns all records from the left table & matched records from the right table. Unmatched records will have NULL values.
SELECT * FROM table1
LEFT JOIN table2 ON table1.column = table2.column;
3. RIGHT JOIN: Returns all records from the right table & matched records from the left table. Unmatched records will have NULL values.
SELECT * FROM table1
RIGHT JOIN table2 ON table1.column = table2.column;
4. FULL JOIN: Returns records when there is a match in either left or right table. Unmatched records will have NULL values.
SELECT * FROM table1
FULL JOIN table2 ON table1.column = table2.column;
4. What is the difference between WHERE & HAVING clauses?
WHERE: Filters records before any groupings are made.
SELECT * FROM table_name
WHERE condition;
HAVING: Filters records after groupings are made.
SELECT column, COUNT(*)
FROM table_name
GROUP BY column
HAVING COUNT(*) > value;
5. How do you calculate average, sum, minimum & maximum values in a column?
Average: SELECT AVG(column_name) FROM table_name;
Sum: SELECT SUM(column_name) FROM table_name;
Minimum: SELECT MIN(column_name) FROM table_name;
Maximum: SELECT MAX(column_name) FROM table_name;
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Hope it helps :) | 356 |
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| 15 | Networking Basics💻📝
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| 16 | 🌐 Frontend Development Concepts You Should Know
Frontend development focuses on building the user interface (UI) of websites and web applications—the part users see and interact with in the browser. It combines design, structure, interactivity, and performance to create responsive and user-friendly web experiences.
1️⃣ Core Technologies of Frontend Development
Frontend development is built on three foundational technologies:
- HTML (HyperText Markup Language): provides the structure of a webpage
- CSS (Cascading Style Sheets): controls the visual appearance and layout
- JavaScript: adds interactivity and dynamic behavior to web pages
2️⃣ Important Frontend Concepts
- Responsive Design: ensures websites work properly across devices
- DOM (Document Object Model): represents the structure of a webpage as objects
- Event Handling: frontend applications respond to user actions
- Asynchronous Programming: fetch data without reloading pages
3️⃣ Frontend Frameworks & Libraries
- React: popular JavaScript library for building component-based UI
- Angular: full frontend framework for large-scale applications
- Vue.js: lightweight framework known for simplicity and flexibility
4️⃣ Styling Tools
- CSS Frameworks: Tailwind CSS, Bootstrap, Material UI
- CSS Preprocessors: Sass, Less
5️⃣ Frontend Development Tools
- VS Code: code editor
- Git: version control
- Webpack / Vite: module bundlers
- NPM / Yarn: package managers
- Chrome DevTools: debugging
6️⃣ Performance Optimization
- lazy loading
- code splitting
- image optimization
- caching strategies
- minimizing HTTP requests
7️⃣ Typical Frontend Development Workflow
1. UI/UX Design
2. HTML Structure
3. Styling with CSS
4. Add JavaScript Interactivity
5. Integrate APIs
6. Test and debug
7. Deploy application
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- Responsive Portfolio Website
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| 20 | 30-day roadmap to learn Python up to an intermediate level
Week 1: Python Basics
*Day 1-2:*
- Learn about Python, its syntax, and how to install Python on your computer.
- Write your first "Hello, World!" program.
- Understand variables and data types (integers, floats, strings).
*Day 3-4:*
- Explore basic operations (arithmetic, string concatenation).
- Learn about user input and how to use the input() function.
- Practice creating and using variables.
*Day 5-7:*
- Dive into control flow with if statements, else statements, and loops (for and while).
- Work on simple programs that involve conditions and loops.
Week 2: Functions and Modules
*Day 8-9:*
- Study functions and how to define your own functions using def.
- Learn about function arguments and return values.
*Day 10-12:*
- Explore built-in functions and libraries (e.g., len(), random, math).
- Understand how to import modules and use their functions.
*Day 13-14:*
- Practice writing functions for common tasks.
- Create a small project that utilizes functions and modules.
Week 3: Data Structures
*Day 15-17:*
- Learn about lists and their operations (slicing, appending, removing).
- Understand how to work with lists of different data types.
*Day 18-19:*
- Study dictionaries and their key-value pairs.
- Practice manipulating dictionary data.
*Day 20-21:*
- Explore tuples and sets.
- Understand when and how to use each data structure.
Week 4: Intermediate Topics
*Day 22-23:*
- Study file handling and how to read/write files in Python.
- Work on projects involving file operations.
*Day 24-26:*
- Learn about exceptions and error handling.
- Explore object-oriented programming (classes and objects).
*Day 27-28:*
- Dive into more advanced topics like list comprehensions and generators.
- Study Python's built-in libraries for web development (e.g., requests).
*Day 29-30:*
- Explore additional libraries and frameworks relevant to your interests (e.g., NumPy for data analysis, Flask for web development, or Pygame for game development).
- Work on a more complex project that combines your knowledge from the past weeks.
Throughout the 30 days, practice coding daily, and don't hesitate to explore Python's documentation and online resources for additional help. Learning Python is a dynamic process, so adapt the roadmap based on your progress and interests.
Best Programming Resources: https://topmate.io/coding/886839
ENJOY LEARNING 👍👍 | 644 |
现已上线!2025 年 Telegram 研究 — 年度关键洞察 
