Artificial Intelligence & ChatGPT Prompts
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๐Ÿ”“Unlock Your Coding Potential with ChatGPT
๐Ÿš€ Your Ultimate Guide to Ace Coding Interviews!
๐Ÿ’ป Coding tips, practice questions, and expert advice to land your dream tech job.


For Promotions: @love_data
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๐ŸŽ“๐Ÿฑ ๐—™๐—ฅ๐—˜๐—˜ ๐—œ๐—•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 ๐Ÿš€

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๐ŸŒ Frontend Development Concepts You Should Know

Frontend development focuses on building the user interface (UI) of websites and web applicationsโ€”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.

1๏ธโƒฃ 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๏ธโƒฃ 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๏ธโƒฃ 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๏ธโƒฃ Styling Tools

- CSS Frameworks: Tailwind CSS, Bootstrap, Material UI
- CSS Preprocessors: Sass, Less

5๏ธโƒฃ Frontend Development Tools

- VS Code: code editor
- Git: version control
- Webpack / Vite: module bundlers
- NPM / Yarn: package managers
- Chrome DevTools: debugging

6๏ธโƒฃ Performance Optimization

- lazy loading
- code splitting
- image optimization
- caching strategies
- minimizing HTTP requests

7๏ธโƒฃ 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๏ธโƒฃ Real-World Frontend Projects

- Responsive Portfolio Website
- Weather App
- To-Do List Application
- E-commerce Product Page
- Dashboard UI

Double Tap โ™ฅ๏ธ For More
โค6
Networking Basics๐Ÿ’ป๐Ÿ“
โค1
๐——๐—ฎ๐˜๐—ฎ ๐—ฆ๐—ฐ๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ ๐—™๐—ฅ๐—˜๐—˜ ๐—ข๐—ป๐—น๐—ถ๐—ป๐—ฒ ๐— ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ๐—ฐ๐—น๐—ฎ๐˜€๐˜€ ๐Ÿ˜

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Date & Time :- 19th June 2026 , 7:00 PM
Most Asked SQL Interview Questions at MAANG Companies๐Ÿ”ฅ๐Ÿ”ฅ

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 Resources๐Ÿ‘‡
https://t.me/mysqldata

Like this post if you need more ๐Ÿ‘โค๏ธ

Hope it helps :)
โค2
๐Ÿ“Š ๐—–๐—ถ๐˜€๐—ฐ๐—ผ 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—ป๐—ฟ๐—ผ๐—น๐—น ๐—ก๐—ผ๐˜„! ๐Ÿš€

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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
โค1
๐——๐—ฎ๐˜๐—ฎ ๐—ฆ๐—ฐ๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ ๐˜„๐—ถ๐˜๐—ต ๐—”๐—œ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ | ๐Ÿญ๐Ÿฌ๐Ÿฌ% ๐—๐—ผ๐—ฏ ๐—”๐˜€๐˜€๐—ถ๐˜€๐˜๐—ฎ๐—ป๐—ฐ๐—ฒ๐Ÿ˜

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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.

โ€ข All LeetCode Articles on Coding Patterns Summarized
https://leetcode.com/discuss/interview-question/5366542/all-leetcode-articles-on-coding-patterns-summarized-in-one-page

โ€ข Solved All Two Pointers Problems in 100 Days
https://leetcode.com/discuss/study-guide/1688903/Solved-all-two-pointers-problems-in-100-days

โ€ข Tree Question Pattern 2023 โ€” Tree Study Guide
https://leetcode.com/discuss/study-guide/2879240/tree-question-pattern-2023-tree-study-guide

โ€ข Important and Useful Links from All Over LeetCode
https://leetcode.com/discuss/general-discussion/665604/Important-and-Useful-links-from-all-over-the-LeetCode

โ€ข Coding Interview Preparation Problems for Beginners
https://leetcode.com/discuss/interview-question/448284/Coding-Interview-preparation-problems-for-beginners

2. Preparation for Companies

โ€ข Google, Meta, Apple, Amazon Senior SDE Preparation
https://prachub.com/?sort=hot&company=Meta%2CGoogle%2CTikTok%2CAmazon

โ€ข A Study Guide for Passing the Google Interview
https://prachub.com/interview-guide

The author also made a small tracker for preparation:

โ€ข company-specific questions
โ€ข Todo / Solved / Revision statuses
โ€ข automatic repetition scheduling
โ€ข AI assistant with hints instead of ready-made solutions

https://prachub.com/questions

3. System Design (HLD)

Instead of random articles โ€” structured collections:

โ€ข Arch 25 โ€” the most common systems and patterns
โ€ข Arch 50 โ€” infrastructure, data, and fault tolerance
โ€ข Arch 75 โ€” more complex scenarios and company-specific specialization
โ€ข Arch All โ€” a full bank of 103 HLD tasks
โ€ข Core Concepts โ€” 33 breakdowns of distributed systems

4. Machine Coding / LLD

Many underestimate this part until their first interview failure.

โ€ข MaCo 30 โ€” the most common tasks
โ€ข MaCo 60 โ€” an extended collection
โ€ข MaCo All โ€” a full set of 103 tasks
โ€ข Design Patterns โ€” 31 design patterns
โค1
๐Ÿš€ ๐—ง๐—ผ๐—ฝ ๐— ๐—ถ๐—ฐ๐—ฟ๐—ผ๐˜€๐—ผ๐—ณ๐˜ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป๐˜€ ๐—ฌ๐—ผ๐˜‚ ๐—–๐—ฎ๐—ป ๐—Ÿ๐—ฒ๐—ฎ๐—ฟ๐—ป ๐—ณ๐—ผ๐—ฟ ๐—™๐—ฅ๐—˜๐—˜! ๐Ÿ’ผ๐Ÿ”ฅ

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๐Ÿ”น Placement Ready in 3 Months! ๐Ÿ”น

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 ๐Ÿ‘‡๐Ÿ‘‡ https://topmate.io/coding/951517

All the best ๐Ÿ‘๐Ÿ‘
โค1
๐—”๐—ฐ๐—ฐ๐—ฒ๐—ป๐˜๐˜‚๐—ฟ๐—ฒ ๐—™๐—ฅ๐—˜๐—˜ ๐—ฉ๐—ถ๐—ฟ๐˜๐˜‚๐—ฎ๐—น ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐—ป๐˜€๐—ต๐—ถ๐—ฝ ๐—ณ๐—ผ๐—ฟ ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ ๐˜„๐—ถ๐˜๐—ต ๐—™๐—ฟ๐—ฒ๐—ฒ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ฒ ๐Ÿ“Š

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How to send follow up email to a recruiter ๐Ÿ‘‡๐Ÿ‘‡

Dear [Recruiterโ€™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 itโ€™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 donโ€™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)
๐—ฃ๐—ฎ๐˜† ๐—”๐—ณ๐˜๐—ฒ๐—ฟ ๐—ฃ๐—น๐—ฎ๐—ฐ๐—ฒ๐—บ๐—ฒ๐—ป๐˜ - ๐—™๐˜‚๐—น๐—น๐˜€๐˜๐—ฎ๐—ฐ๐—ธ๐——๐—ฒ๐˜ƒ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—ช๐—ถ๐˜๐—ต ๐—š๐—ฒ๐—ป๐—”๐—œ ๐Ÿ˜

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โค1
๐Ÿ”ฐ Anonymous function in Python.
โค1
๐Ÿณ 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—ง๐—ผ ๐—˜๐—ป๐—ฟ๐—ผ๐—น๐—น ๐—œ๐—ป ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฒ๐Ÿ˜ 

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๐ŸŽ“ 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 ๐Ÿš€

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โœ… Today's AI News

1๏ธโƒฃ Big AI platforms are still expanding
Google is pushing Gemini and related AI tools, while OpenAI continues to frame its work around safe, beneficial AGI.

2๏ธโƒฃ AI education and explainers are still in demand
Current explainers from major sources continue to define AI as systems that can learn, reason, and handle tasks like speech recognition and image analysis.

3๏ธโƒฃ AI assistants remain a major consumer focus
Writing, planning, brainstorming, research, image creation, and video creation are still central use cases for consumer AI products.

4๏ธโƒฃ AI detection is growing
Tools that check whether text was AI-generated are now a visible part of the ecosystem.

5๏ธโƒฃ The AI ecosystem stays broad
AI continues to cut across software, search, productivity, automation, cloud platforms, and research labs.

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