Artificial Intelligence & ChatGPT Prompts
๐Unlock Your Coding Potential with ChatGPT ๐ Your Ultimate Guide to Ace Coding Interviews! ๐ป Coding tips, practice questions, and expert advice to land your dream tech job. For Promotions: @love_data
Ko'proq ko'rsatish๐ Telegram kanali Artificial Intelligence & ChatGPT Prompts analitikasi
Artificial Intelligence & ChatGPT Prompts (@curiousprogrammer) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 42 100 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 3 208-o'rinni va Hindiston mintaqasida 9 253-o'rinni egallagan.
๐ Auditoriya koโrsatkichlari va dinamika
ะฝะตะฒัะดะพะผะพ sanasidan buyon loyiha tez oโsib, 42 100 obunachiga ega boโldi.
23 Iyun, 2026 dagi oxirgi maโlumotlarga koโra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 129 ga, soโnggi 24 soatda esa -20 ga oโzgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya oโrtacha 1.84% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 0.43% ini tashkil etuvchi reaksiyalarni toโplaydi.
- Post qamrovi: Har bir post oโrtacha 775 marta koโriladi; birinchi sutkada odatda 183 ta koโrish yigโiladi.
- Reaksiyalar va oโzaro taโsir: Auditoriya faol: har bir postga oโrtacha 3 ta reaksiya keladi.
- Tematik yoโnalishlar: Kontent learning, algorithm, detection, llm, pattern kabi asosiy mavzularga jamlangan.
๐ Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida taโriflaydi:
โ๐Unlock Your Coding Potential with ChatGPT
๐ Your Ultimate Guide to Ace Coding Interviews!
๐ป Coding tips, practice questions, and expert advice to land your dream tech job.
For Promotions: @love_dataโ
Yuqori yangilanish chastotasi (oxirgi maโlumot 24 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli boโlib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim taโsir nuqtasiga aylantirishini koโrsatadi.
Ma'lumot yuklanmoqda...
| Sana | Obunachilarni jalb qilish | Esdaliklar | Kanallar | |
| 23 Iyun | +5 | |||
| 22 Iyun | 0 | |||
| 21 Iyun | 0 | |||
| 20 Iyun | 0 | |||
| 19 Iyun | +9 | |||
| 18 Iyun | +1 | |||
| 17 Iyun | +2 | |||
| 16 Iyun | +8 | |||
| 15 Iyun | +8 | |||
| 14 Iyun | +13 | |||
| 13 Iyun | +20 | |||
| 12 Iyun | +13 | |||
| 11 Iyun | +1 | |||
| 10 Iyun | +9 | |||
| 09 Iyun | +7 | |||
| 08 Iyun | +7 | |||
| 07 Iyun | +10 | |||
| 06 Iyun | +4 | |||
| 05 Iyun | +23 | |||
| 04 Iyun | +7 | |||
| 03 Iyun | +13 | |||
| 02 Iyun | +17 | |||
| 01 Iyun | +3 |
| 2 | ๐ฐ Anonymous function in Python. | 347 |
| 3 | ๐ฃ๐ฎ๐ ๐๐ณ๐๐ฒ๐ฟ ๐ฃ๐น๐ฎ๐ฐ๐ฒ๐บ๐ฒ๐ป๐ - ๐๐๐น๐น๐๐๐ฎ๐ฐ๐ธ๐๐ฒ๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐ช๐ถ๐๐ต ๐๐ฒ๐ป๐๐ ๐
Curriculum designed and taught by alumni from IITs & leading tech companies.
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Hurry! Limited seats are available.๐โโ๏ธ | 327 |
| 4 | How to send follow up email to a recruiter ๐๐
Dear [Recruiterโs 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 itโs 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 donโt 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 | ๐๐ฐ๐ฐ๐ฒ๐ป๐๐๐ฟ๐ฒ ๐๐ฅ๐๐ ๐ฉ๐ถ๐ฟ๐๐๐ฎ๐น ๐๐ป๐๐ฒ๐ฟ๐ป๐๐ต๐ถ๐ฝ ๐ณ๐ผ๐ฟ ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐ ๐๐ถ๐๐ต ๐๐ฟ๐ฒ๐ฒ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ฒ ๐
Join the Accenture Virtual Internship Program and learn industry-relevant analytics skills with a free certificate ๐
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๐ฅ Start your Data Analytics journey today and gain valuable virtual internship experience from a top global company. | 327 |
| 6 | ๐น Placement Ready in 3 Months! ๐น
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
3. Months 1, 2, & 3: Coding
- Data Structures and Algorithms (DSA)
- Practice on platforms like Hackerrank, Codechef, and Leetcode
4. Projects, Skills, and Internships
- Full-stack or ML projects
- Internship experiences and interview prep
5. Month 3: Mock Interviews
- Practice with Pramp and peers
Top Coding Interview Resources to prepare for Microsoft, Amazon, Meta, Apple, Adobe, VMware, Visa, Twitter, LinkedIn, JP Morgan, Goldman Sachs, Oracle and Walmart ๐๐ https://topmate.io/coding/951517
All the best ๐๐ | 324 |
| 7 | ๐ ๐ง๐ผ๐ฝ ๐ ๐ถ๐ฐ๐ฟ๐ผ๐๐ผ๐ณ๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป๐ ๐ฌ๐ผ๐ ๐๐ฎ๐ป ๐๐ฒ๐ฎ๐ฟ๐ป ๐ณ๐ผ๐ฟ ๐๐ฅ๐๐! ๐ผ๐ฅ
These free courses can help you build in-demand tech skills for 2026 ๐
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๐ฅ Start learning today and future-proof your career with Microsoft-certified skills. | 317 |
| 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.
โข All LeetCode Articles on Coding Patterns Summarized
https://leetcode.com/discuss/interview-question/5366542/all-leetcode-articles-on-coding-patterns-summarized-in-one-page
โข Solved All Two Pointers Problems in 100 Days
https://leetcode.com/discuss/study-guide/1688903/Solved-all-two-pointers-problems-in-100-days
โข Tree Question Pattern 2023 โ Tree Study Guide
https://leetcode.com/discuss/study-guide/2879240/tree-question-pattern-2023-tree-study-guide
โข Important and Useful Links from All Over LeetCode
https://leetcode.com/discuss/general-discussion/665604/Important-and-Useful-links-from-all-over-the-LeetCode
โข Coding Interview Preparation Problems for Beginners
https://leetcode.com/discuss/interview-question/448284/Coding-Interview-preparation-problems-for-beginners
2. Preparation for Companies
โข Google, Meta, Apple, Amazon Senior SDE Preparation
https://prachub.com/?sort=hot&company=Meta%2CGoogle%2CTikTok%2CAmazon
โข A Study Guide for Passing the Google Interview
https://prachub.com/interview-guide
The author also made a small tracker for preparation:
โข company-specific questions
โข Todo / Solved / Revision statuses
โข automatic repetition scheduling
โข AI assistant with hints instead of ready-made solutions
https://prachub.com/questions
3. System Design (HLD)
Instead of random articles โ structured collections:
โข Arch 25 โ the most common systems and patterns
โข Arch 50 โ infrastructure, data, and fault tolerance
โข Arch 75 โ more complex scenarios and company-specific specialization
โข Arch All โ a full bank of 103 HLD tasks
โข Core Concepts โ 33 breakdowns of distributed systems
4. Machine Coding / LLD
Many underestimate this part until their first interview failure.
โข MaCo 30 โ the most common tasks
โข MaCo 60 โ an extended collection
โข MaCo All โ a full set of 103 tasks
โข Design Patterns โ 31 design patterns | 350 |
| 9 | ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ ๐๐ถ๐๐ต ๐๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ | ๐ญ๐ฌ๐ฌ% ๐๐ผ๐ฏ ๐๐๐๐ถ๐๐๐ฎ๐ป๐ฐ๐ฒ๐
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Hurry Up ๐โโ๏ธ! Limited seats are available. | 312 |
| 10 | AI/ML roadmap
Topic: Mathematics
- Subtopic: Linear Algebra
- Vectors, Matrices, Eigenvalues and Eigenvectors
- Subtopic: Calculus
- Differentiation, Integration, Partial Derivatives
- 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 | ๐ ๐๐ถ๐๐ฐ๐ผ ๐๐ฅ๐๐ ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป | ๐๐ป๐ฟ๐ผ๐น๐น ๐ก๐ผ๐! ๐
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| 12 | Most Asked SQL Interview Questions at MAANG Companies๐ฅ๐ฅ
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;
Here you can find essential SQL Interview Resources๐
https://t.me/mysqldata
Like this post if you need more ๐โค๏ธ
Hope it helps :) | 356 |
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| 15 | Networking Basics๐ป๐
#techinfo | 303 |
| 16 | ๐ Frontend Development Concepts You Should Know
Frontend development focuses on building the user interface (UI) of websites and web applicationsโthe part users see and interact with in the browser. It combines design, structure, interactivity, and performance to create responsive and user-friendly web experiences.
1๏ธโฃ 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
2๏ธโฃ 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
3๏ธโฃ 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
4๏ธโฃ Styling Tools
- CSS Frameworks: Tailwind CSS, Bootstrap, Material UI
- CSS Preprocessors: Sass, Less
5๏ธโฃ Frontend Development Tools
- VS Code: code editor
- Git: version control
- Webpack / Vite: module bundlers
- NPM / Yarn: package managers
- Chrome DevTools: debugging
6๏ธโฃ Performance Optimization
- lazy loading
- code splitting
- image optimization
- caching strategies
- minimizing HTTP requests
7๏ธโฃ 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
8๏ธโฃ Real-World Frontend Projects
- Responsive Portfolio Website
- Weather App
- To-Do List Application
- E-commerce Product Page
- Dashboard UI
Double Tap โฅ๏ธ For More | 384 |
| 17 | ๐๐ฑ ๐๐ฅ๐๐ ๐๐๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐ฎ๐ฌ๐ฎ๐ฒ ๐
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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 ๐๐ | 644 |
Endi mavjud! Telegram Tadqiqoti 2025 โ yilning asosiy insaytlari 
