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Artificial Intelligence & ChatGPT Prompts

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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๐Ÿ“ˆ Analytical overview of Telegram channel Artificial Intelligence & ChatGPT Prompts

Channel Artificial Intelligence & ChatGPT Prompts (@curiousprogrammer) in the English language segment is an active participant. Currently, the community unites 42 123 subscribers, ranking 3 229 in the Technologies & Applications category and 9 545 in the India region.

๐Ÿ“Š Audience metrics and dynamics

Since its creation on ะฝะตะฒั–ะดะพะผะพ, the project has demonstrated rapid growth, gathering an audience of 42 123 subscribers.

According to the latest data from 12 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 175 over the last 30 days and by 12 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 2.43%. Within the first 24 hours after publication, content typically collects 0.73% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 1 024 views. Within the first day, a publication typically gains 306 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 3.
  • Thematic interests: Content is focused on key topics such as learning, algorithm, detection, llm, pattern.

๐Ÿ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
โ€œ๐Ÿ”“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_dataโ€

Thanks to the high frequency of updates (latest data received on 13 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.

42 123
Subscribers
+1224 hours
+227 days
+17530 days
Posts Archive
๐Ÿฒ ๐—™๐—ฟ๐—ฒ๐—ฒ ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐˜๐—ผ ๐—Ÿ๐—ฒ๐—ฎ๐—ฟ๐—ป ๐˜๐—ต๐—ฒ ๐— ๐—ผ๐˜€๐˜ ๐—œ๐—ป-๐——๐—ฒ๐—บ๐—ฎ๐—ป๐—ฑ ๐—ง๐—ฒ๐—ฐ๐—ต ๐—ฆ๐—ธ๐—ถ๐—น๐—น๐˜€๐Ÿ˜ ๐Ÿš€ Want to future-proof
๐Ÿฒ ๐—™๐—ฟ๐—ฒ๐—ฒ ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐˜๐—ผ ๐—Ÿ๐—ฒ๐—ฎ๐—ฟ๐—ป ๐˜๐—ต๐—ฒ ๐— ๐—ผ๐˜€๐˜ ๐—œ๐—ป-๐——๐—ฒ๐—บ๐—ฎ๐—ป๐—ฑ ๐—ง๐—ฒ๐—ฐ๐—ต ๐—ฆ๐—ธ๐—ถ๐—น๐—น๐˜€๐Ÿ˜ ๐Ÿš€ Want to future-proof your career without spending a single rupee?๐Ÿ’ต These 6 free online courses from top institutions like Google, Harvard, IBM, Stanford, and Cisco will help you master high-demand tech skills in 2025 โ€” from Data Analytics to Machine Learning๐Ÿ“Š๐Ÿง‘โ€๐Ÿ’ป ๐‹๐ข๐ง๐ค๐Ÿ‘‡:- https://pdlink.in/4fbDejW Each course is beginner-friendly, comes with certification, and helps you build your resume or switch careersโœ…๏ธ

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๐—ง๐—ผ๐—ฝ ๐—–๐—ผ๐—บ๐—ฝ๐—ฎ๐—ป๐—ถ๐—ฒ๐˜€ ๐—›๐—ถ๐—ฟ๐—ถ๐—ป๐—ด ๐—”๐—ฐ๐—ฟ๐—ผ๐˜€๐˜€ ๐—œ๐—ป๐—ฑ๐—ถ๐—ฎ ๐Ÿ˜ Multiple top MNCs are hiring for various roles across domains! ๐Ÿ”น Roles: Tech & Non-Tech ๐Ÿ”น Location: PAN India ๐Ÿ”น Qualification: Graduate / Post Graduate ๐Ÿ”น Salary: Competitive Packages ๐—”๐—ฝ๐—ฝ๐—น๐˜† ๐—ก๐—ผ๐˜„๐Ÿ‘‡:- https://bit.ly/4f5VAmj Select your experience & Complete The Registration Process  Select the company name & apply for the role that matches you

JOINS Definition Joins in MySQL allow you to retrieve data from two or more tables based on a related column. They are used to combine rows from multiple tables. Types of Joins 1. INNER JOIN: - Returns rows where there is a match in both tables. - Syntax:
            SELECT columns
            FROM table1
            INNER JOIN table2
            ON table1.column = table2.column;
            
- Example:
            SELECT employees.name, departments.name
            FROM employees
            INNER JOIN departments
            ON employees.department_id = departments.id;
            
2. LEFT JOIN (OUTER JOIN): - Returns all rows from the left table and matching rows from the right table. Non-matching rows have NULL. - Example:
            SELECT employees.name, departments.name
            FROM employees
            LEFT JOIN departments
            ON employees.department_id = departments.id;
            
3. RIGHT JOIN (OUTER JOIN): - Returns all rows from the right table and matching rows from the left table. Non-matching rows have NULL. - Example:
            SELECT employees.name, departments.name
            FROM employees
            RIGHT JOIN departments
            ON employees.department_id = departments.id;         
4. FULL OUTER JOIN: - Returns all rows from both tables, matching where possible. Not natively supported in MySQL, but can be simulated using UNION. - Example:
            SELECT employees.name, departments.name
            FROM employees
            LEFT JOIN departments
            ON employees.department_id = departments.id
            
            UNION
            
            SELECT employees.name, departments.name
            FROM employees
            RIGHT JOIN departments
            ON employees.department_id = departments.id;
5. CROSS JOIN: - Returns the Cartesian product of both tables. - Example:
            SELECT employees.name, departments.name
            FROM employees
            CROSS JOIN departments;
Interview Questions 1. What is the difference between INNER JOIN and OUTER JOIN? - INNER JOIN only includes rows with matches in both tables, while OUTER JOIN includes unmatched rows. 2. How can you simulate a FULL OUTER JOIN in MySQL? - Use UNION of LEFT JOIN and RIGHT JOIN. 3. What is a Cartesian product, and when does it occur? - A Cartesian product occurs in a CROSS JOIN or when no ON condition is specified, resulting in all possible row combinations.

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๐Ÿš€ Coding Projects & Ideas ๐Ÿ’ป Inspire your next portfolio project โ€” from beginner to pro! ๐Ÿ—๏ธ Beginner-Friendly Projects 1๏ธโƒฃ To-Do List App โ€“ Create tasks, mark as done, store in browser. 2๏ธโƒฃ Weather App โ€“ Fetch live weather data using a public API. 3๏ธโƒฃ Unit Converter โ€“ Convert currencies, length, or weight. 4๏ธโƒฃ Personal Portfolio Website โ€“ Showcase skills, projects & resume. 5๏ธโƒฃ Calculator App โ€“ Build a clean UI for basic math operations. โš™๏ธ Intermediate Projects 6๏ธโƒฃ Chatbot with AI โ€“ Use NLP libraries to answer user queries. 7๏ธโƒฃ Stock Market Tracker โ€“ Real-time graphs & stock performance. 8๏ธโƒฃ Expense Tracker โ€“ Manage budgets & visualize spending. 9๏ธโƒฃ Image Classifier (ML) โ€“ Classify objects using pre-trained models. ๐Ÿ”Ÿ E-Commerce Website โ€“ Product catalog, cart, payment gateway. ๐Ÿš€ Advanced Projects 1๏ธโƒฃ1๏ธโƒฃ Blockchain Voting System โ€“ Decentralized & tamper-proof elections. 1๏ธโƒฃ2๏ธโƒฃ Social Media Analytics Dashboard โ€“ Analyze engagement, reach & sentiment. 1๏ธโƒฃ3๏ธโƒฃ AI Code Assistant โ€“ Suggest code improvements or detect bugs. 1๏ธโƒฃ4๏ธโƒฃ IoT Smart Home App โ€“ Control devices using sensors and Raspberry Pi. 1๏ธโƒฃ5๏ธโƒฃ AR/VR Simulation โ€“ Build immersive learning or game experiences. ๐Ÿ’ก Tip: Build in public. Share your process on GitHub, LinkedIn & Twitter. ๐Ÿ”ฅ React โค๏ธ for more project ideas!

Repost from Data Analyst Jobs
๐—™๐—ฅ๐—˜๐—˜ ๐—ข๐—ป๐—น๐—ถ๐—ป๐—ฒ ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐—ง๐—ผ ๐—˜๐—ป๐—ฟ๐—ผ๐—น๐—น ๐—œ๐—ป ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฑ ๐Ÿ˜ Learn Fundamental Skills with Free Online Courses & E
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Accenture Data Scientist Interview Questions! 1st round- Technical Round - 2 SQl questions based on playing around views and table, which could be solved by both subqueries and window functions. - 2 Pandas questions , testing your knowledge on filtering , concatenation , joins and merge. - 3-4 Machine Learning questions completely based on my Projects, starting from Explaining the problem statements and then discussing the roadblocks of those projects and some cross questions. 2nd round- - Couple of python questions agains on pandas and numpy and some hypothetical data. - Machine Learning projects explanations and cross questions. - Case Study and a quiz question. 3rd and Final round. HR interview Simple Scenerio Based Questions. Data Science Resources ๐Ÿ‘‡๐Ÿ‘‡ https://t.me/datasciencefun Like if you need similar content ๐Ÿ˜„๐Ÿ‘

๐—ฆ๐˜๐—ถ๐—น๐—น ๐—™๐—ฎ๐—ถ๐—น๐—ถ๐—ป๐—ด ๐—ง๐—ฒ๐—ฐ๐—ต ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฒ๐˜„๐˜€? ๐—ง๐—ต๐—ฒ๐˜€๐—ฒ ๐Ÿฏ ๐—™๐—ฟ๐—ฒ๐—ฒ ๐—ฅ๐—ฒ๐˜€๐—ผ๐˜‚๐—ฟ๐—ฐ๐—ฒ๐˜€ ๐—–๐—ผ๐˜‚๐—น๐—ฑ ๐—™๐—ถ๐—ป๐—ฎ๐—น๐—น๐˜†
๐—ฆ๐˜๐—ถ๐—น๐—น ๐—™๐—ฎ๐—ถ๐—น๐—ถ๐—ป๐—ด ๐—ง๐—ฒ๐—ฐ๐—ต ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฒ๐˜„๐˜€? ๐—ง๐—ต๐—ฒ๐˜€๐—ฒ ๐Ÿฏ ๐—™๐—ฟ๐—ฒ๐—ฒ ๐—ฅ๐—ฒ๐˜€๐—ผ๐˜‚๐—ฟ๐—ฐ๐—ฒ๐˜€ ๐—–๐—ผ๐˜‚๐—น๐—ฑ ๐—™๐—ถ๐—ป๐—ฎ๐—น๐—น๐˜† ๐—–๐—ต๐—ฎ๐—ป๐—ด๐—ฒ ๐—ง๐—ต๐—ฎ๐˜๐Ÿ˜ Youโ€™ve spent hours solving LeetCode problems. Youโ€™ve gone through entire DSA playlists๐Ÿ—ฃโœจ๏ธ The internet is filled with confusing roadmaps and endless practice sets. But what you need is clarity, structure, and confidence. Thatโ€™s exactly what these 3 high-impact, free YouTube videos give you.๐Ÿ‘จโ€๐Ÿ’ป๐Ÿ“Œ ๐‹๐ข๐ง๐ค๐Ÿ‘‡:- https://pdlink.in/4feEnaA This is your new cheat codeโœ…๏ธ

โญ Beginner To Advanced FULLSTACK
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PYTHON SYNTAX
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๐Ÿฑ ๐—ฅ๐—ฒ๐—ฎ๐—น-๐—ช๐—ผ๐—ฟ๐—น๐—ฑ ๐—ง๐—ฒ๐—ฐ๐—ต ๐—ฃ๐—ฟ๐—ผ๐—ท๐—ฒ๐—ฐ๐˜๐˜€ ๐˜๐—ผ ๐—•๐˜‚๐—ถ๐—น๐—ฑ ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐—ฅ๐—ฒ๐˜€๐˜‚๐—บ๐—ฒ โ€“ ๐—ช๐—ถ๐˜๐—ต ๐—™๐˜‚๐—น๐—น ๐—ง๐˜‚๐˜๐—ผ๐—ฟ๐—ถ๐—ฎ๐—น๐˜€!๐Ÿ˜ Are you ready to build real-world tech projects that donโ€™t just look good on your resume, but actually teach you practical, job-ready skills?๐Ÿง‘โ€๐Ÿ’ป๐Ÿ“Œ Hereโ€™s a curated list of 5 high-value development tutorials โ€” covering everything from full-stack development and real-time chat apps to AI form builders and reinforcement learningโœจ๏ธ๐Ÿ’ป ๐‹๐ข๐ง๐ค๐Ÿ‘‡:- https://pdlink.in/3UtCSLO Theyโ€™re real, portfolio-worthy projects you can start todayโœ…๏ธ

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Guide to Building an AI Agent 1๏ธโƒฃ ๐—–๐—ต๐—ผ๐—ผ๐˜€๐—ฒ ๐˜๐—ต๐—ฒ ๐—ฅ๐—ถ๐—ด๐—ต๐˜ ๐—Ÿ๐—Ÿ๐—  Not all LLMs are equal. Pick one that: - Excels in reasoning benchmarks - Supports chain-of-thought (CoT) prompting - Delivers consistent responses ๐Ÿ“Œ Tip: Experiment with models & fine-tune prompts to enhance reasoning. 2๏ธโƒฃ ๐——๐—ฒ๐—ณ๐—ถ๐—ป๐—ฒ ๐˜๐—ต๐—ฒ ๐—”๐—ด๐—ฒ๐—ป๐˜โ€™๐˜€ ๐—–๐—ผ๐—ป๐˜๐—ฟ๐—ผ๐—น ๐—Ÿ๐—ผ๐—ด๐—ถ๐—ฐ Your agent needs a strategy: - Tool Use: Call tools when needed; otherwise, respond directly. - Basic Reflection: Generate, critique, and refine responses. - ReAct: Plan, execute, observe, and iterate. - Plan-then-Execute: Outline all steps first, then execute. ๐Ÿ“Œ Choosing the right approach improves reasoning & reliability. 3๏ธโƒฃ ๐——๐—ฒ๐—ณ๐—ถ๐—ป๐—ฒ ๐—–๐—ผ๐—ฟ๐—ฒ ๐—œ๐—ป๐˜€๐˜๐—ฟ๐˜‚๐—ฐ๐˜๐—ถ๐—ผ๐—ป๐˜€ & ๐—™๐—ฒ๐—ฎ๐˜๐˜‚๐—ฟ๐—ฒ๐˜€ Set operational rules: - How to handle unclear queries? (Ask clarifying questions) - When to use external tools? - Formatting rules? (Markdown, JSON, etc.) - Interaction style? ๐Ÿ“Œ Clear system prompts shape agent behavior. 4๏ธโƒฃ ๐—œ๐—บ๐—ฝ๐—น๐—ฒ๐—บ๐—ฒ๐—ป๐˜ ๐—ฎ ๐— ๐—ฒ๐—บ๐—ผ๐—ฟ๐˜† ๐—ฆ๐˜๐—ฟ๐—ฎ๐˜๐—ฒ๐—ด๐˜† LLMs forget past interactions. Memory strategies: - Sliding Window: Retain recent turns, discard old ones. - Summarized Memory: Condense key points for recall. - Long-Term Memory: Store user preferences for personalization. ๐Ÿ“Œ Example: A financial AI recalls risk tolerance from past chats. 5๏ธโƒฃ ๐—˜๐—พ๐˜‚๐—ถ๐—ฝ ๐˜๐—ต๐—ฒ ๐—”๐—ด๐—ฒ๐—ป๐˜ ๐˜„๐—ถ๐˜๐—ต ๐—ง๐—ผ๐—ผ๐—น๐˜€ & ๐—”๐—ฃ๐—œ๐˜€ Extend capabilities with external tools: - Name: Clear, intuitive (e.g., "StockPriceRetriever") - Description: What does it do? - Schemas: Define input/output formats - Error Handling: How to manage failures? ๐Ÿ“Œ Example: A support AI retrieves order details via CRM API. 6๏ธโƒฃ ๐——๐—ฒ๐—ณ๐—ถ๐—ป๐—ฒ ๐˜๐—ต๐—ฒ ๐—”๐—ด๐—ฒ๐—ป๐˜โ€™๐˜€ ๐—ฅ๐—ผ๐—น๐—ฒ & ๐—ž๐—ฒ๐˜† ๐—ง๐—ฎ๐˜€๐—ธ๐˜€ Narrowly defined agents perform better. Clarify: - Mission: (e.g., "I analyze datasets for insights.") - Key Tasks: (Summarizing, visualizing, analyzing) - Limitations: ("I donโ€™t offer legal advice.") ๐Ÿ“Œ Example: A financial AI focuses on finance, not general knowledge. 7๏ธโƒฃ ๐—›๐—ฎ๐—ป๐—ฑ๐—น๐—ถ๐—ป๐—ด ๐—ฅ๐—ฎ๐˜„ ๐—Ÿ๐—Ÿ๐—  ๐—ข๐˜‚๐˜๐—ฝ๐˜‚๐˜๐˜€ Post-process responses for structure & accuracy: - Convert AI output to structured formats (JSON, tables) - Validate correctness before user delivery - Ensure correct tool execution ๐Ÿ“Œ Example: A financial AI converts extracted data into JSON. 8๏ธโƒฃ ๐—ฆ๐—ฐ๐—ฎ๐—น๐—ถ๐—ป๐—ด ๐˜๐—ผ ๐— ๐˜‚๐—น๐˜๐—ถ-๐—”๐—ด๐—ฒ๐—ป๐˜ ๐—ฆ๐˜†๐˜€๐˜๐—ฒ๐—บ๐˜€ (๐—”๐—ฑ๐˜ƒ๐—ฎ๐—ป๐—ฐ๐—ฒ๐—ฑ) For complex workflows: - Info Sharing: What context is passed between agents? - Error Handling: What if one agent fails? - State Management: How to pause/resume tasks? ๐Ÿ“Œ Example: 1๏ธโƒฃ One agent fetches data 2๏ธโƒฃ Another summarizes 3๏ธโƒฃ A third generates a report Master the fundamentals, experiment, and refine and.. now go build something amazing!

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