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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 Telegram kanali Artificial Intelligence & ChatGPT Prompts analitikasi

Artificial Intelligence & ChatGPT Prompts (@curiousprogrammer) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 42 123 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 3 229-o'rinni va Hindiston mintaqasida 9 545-o'rinni egallagan.

๐Ÿ“Š Auditoriya koโ€˜rsatkichlari va dinamika

ะฝะตะฒั–ะดะพะผะพ sanasidan buyon loyiha tez oโ€˜sib, 42 123 obunachiga ega boโ€˜ldi.

12 Iyun, 2026 dagi oxirgi maโ€™lumotlarga koโ€˜ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 175 ga, soโ€˜nggi 24 soatda esa 12 ga oโ€˜zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya oโ€˜rtacha 2.43% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 0.73% ini tashkil etuvchi reaksiyalarni toโ€˜playdi.
  • Post qamrovi: Har bir post oโ€˜rtacha 1 024 marta koโ€˜riladi; birinchi sutkada odatda 306 ta koโ€˜rish yigโ€˜iladi.
  • Reaksiyalar va oโ€˜zaro taโ€™sir: Auditoriya faol: har bir postga oโ€˜rtacha 3 ta reaksiya keladi.
  • Tematik yoโ€˜nalishlar: Kontent learning, algorithm, detection, llm, pattern kabi asosiy mavzularga jamlangan.

๐Ÿ“ Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida taโ€™riflaydi:
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€

Yuqori yangilanish chastotasi (oxirgi maโ€™lumot 13 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli boโ€˜lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim taโ€™sir nuqtasiga aylantirishini koโ€˜rsatadi.

42 123
Obunachilar
+1224 soatlar
+227 kunlar
+17530 kunlar
Postlar arxiv
Deep Learning with Python ๐Ÿ“š book
Deep Learning with Python ๐Ÿ“š book

Twisted Python Projects.pdf7.47 MB

๐—ง๐—ผ๐—ฝ ๐Ÿฑ ๐—ง๐—ฒ๐—ฐ๐—ต๐—ป๐—ผ๐—น๐—ผ๐—ด๐—ถ๐—ฒ๐˜€ ๐—ง๐—ผ ๐— ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ ๐—œ๐—ป ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฑ | ๐—˜๐—ป๐—ฟ๐—ผ๐—น๐—น ๐—™๐—ผ๐—ฟ ๐—™๐—ฅ๐—˜๐—˜ ๐Ÿ˜ Acquire industry-relevan
๐—ง๐—ผ๐—ฝ ๐Ÿฑ ๐—ง๐—ฒ๐—ฐ๐—ต๐—ป๐—ผ๐—น๐—ผ๐—ด๐—ถ๐—ฒ๐˜€ ๐—ง๐—ผ ๐— ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ ๐—œ๐—ป ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฑ | ๐—˜๐—ป๐—ฟ๐—ผ๐—น๐—น ๐—™๐—ผ๐—ฟ ๐—™๐—ฅ๐—˜๐—˜ ๐Ÿ˜  Acquire industry-relevant skills to grow in your career and stand out to prospective employers. ๐—”๐—œ & ๐— ๐—Ÿ :- https://pdlink.in/3U3eZuq ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ :- https://pdlink.in/4lp7hXQ ๐—–๐—น๐—ผ๐˜‚๐—ฑ ๐—–๐—ผ๐—บ๐—ฝ๐˜‚๐˜๐—ถ๐—ป๐—ด :- https://pdlink.in/3GtNJlO ๐—–๐˜†๐—ฏ๐—ฒ๐—ฟ ๐—ฆ๐—ฒ๐—ฐ๐˜‚๐—ฟ๐—ถ๐˜๐˜† :- https://pdlink.in/4nHBuTh ๐—ข๐˜๐—ต๐—ฒ๐—ฟ ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ :- https://pdlink.in/3ImMFAB Enroll For FREE & Get Certified ๐ŸŽ“

Frontend Development Interview Questions Beginner Level 1. What are semantic HTML tags? 2. Difference between id and class in HTML? 3. What is the Box Model in CSS? 4. Difference between margin and padding? 5. What is a responsive web design? 6. What is the use of the <meta viewport> tag? 7. Difference between inline, block, and inline-block elements? 8. What is the difference between == and === in JavaScript? 9. What are arrow functions in JavaScript? 10. What is DOM and how is it used? Intermediate Level 1. What are pseudo-classes and pseudo-elements in CSS? 2. How do media queries work in responsive design? 3. Difference between relative, absolute, fixed, and sticky positioning? 4. What is the event loop in JavaScript? 5. Explain closures in JavaScript with an example. 6. What are Promises and how do you handle errors with .catch()? 7. What is a higher-order function? 8. What is the difference between localStorage and sessionStorage? 9. How does this keyword work in different contexts? 10. What is JSX in React? Advanced Level 1. How does the virtual DOM work in React? 2. What are controlled vs uncontrolled components in React? 3. What is useMemo and when should you use it? 4. How do you optimize a large React app for performance? 5. What are React lifecycle methods (class-based) and their hook equivalents? 6. How does Redux work and when should you use it? 7. What is code splitting and why is it useful? 8. How do you secure a frontend app from XSS attacks? 9. Explain the concept of Server-Side Rendering (SSR) vs Client-Side Rendering (CSR). 10. What are Web Components and how do they work? React โค๏ธ for the detailed answers Join for free resources: ๐Ÿ‘‡ https://whatsapp.com/channel/0029VaiSdWu4NVis9yNEE72z

๐Ÿฑ ๐— ๐˜‚๐˜€๐˜-๐—ช๐—ฎ๐˜๐—ฐ๐—ต ๐—ฉ๐—ถ๐—ฑ๐—ฒ๐—ผ๐˜€ ๐˜๐—ผ ๐— ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ ๐—ถ๐—ป ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฑ (๐—™๐—ฅ๐—˜๐—˜)๐Ÿ˜ Want to become a
๐Ÿฑ ๐— ๐˜‚๐˜€๐˜-๐—ช๐—ฎ๐˜๐—ฐ๐—ต ๐—ฉ๐—ถ๐—ฑ๐—ฒ๐—ผ๐˜€ ๐˜๐—ผ ๐— ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ ๐—ถ๐—ป ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฑ (๐—™๐—ฅ๐—˜๐—˜)๐Ÿ˜ Want to become a Data Analyst in 2025? Start with these 5 game-changing videos! ๐Ÿ“Š This beginner-friendly roadmap covers everything you need โ€” from foundational stats to full project-ready skills. And the best part? Itโ€™s 100% FREE!๐Ÿ‘จโ€๐ŸŽ“โœจ๏ธ ๐‹๐ข๐ง๐ค๐Ÿ‘‡:- https://pdlink.in/40aZ7K3 ๐Ÿ“Œ Save this post. Start your journey today!โœ…๏ธ

Free Resources to Learn Each Tech Stack ๐Ÿง โœจ No excuses. Everything you need is free! 1. Frontend Development โฏ freeCodeCamp.org โ€“ HTML, CSS, JS โฏ MDN Web Docs โ€“ Best docs for web tech โฏ Frontend Mentor โ€“ Real-world challenges โฏ CSS Tricks โ€“ CSS deep dives โฏ YouTube: Kevin Powell, Web Dev Simplified โ€” 2. Backend Development โฏ Node.js Docs โฏ Django Girls Tutorial โฏ The Odin Project โ€“ Full Stack โฏ Spring Boot Guides โฏ YouTube: Amigoscode, CodeWithHarry (Hindi), Tech With Tim โ€” 3. Full-Stack Development โฏ Full Stack Open โ€“ React + Node โฏ The Odin Project โฏ CS50 Web โ€“ Harvardโ€™s free course โฏ YouTube: Traversy Media, Clever Programmer, JavaScript Mastery โ€” 4. Data Analytics โฏ Kaggle Learn โ€“ Python, SQL, Viz โฏ Maven Analytics โ€“ Free Power BI/Tableau projects โฏ Google Data Analytics Course โฏ W3Schools SQL โฏ YouTube: Luke Barousse, Alex The Analyst โ€” 5. Machine Learning โฏ Googleโ€™s ML Crash Course โฏ fast.ai โ€“ Deep learning made easy โฏ Kaggle Courses โ€“ End-to-end ML โฏ Coursera โ€“ Andrew Ng โฏ YouTube: StatQuest, Krish Naik, Codebasics โ€” 6. DevOps โฏ KodeKloud โ€“ Docker, K8s, Ansible โฏ Learn Git Branching โฏ Katacoda โ€“ Interactive Linux & DevOps โฏ Roadmap.sh โ€“ What to learn โฏ YouTube: TechWorld with Nana, Nana Janashia

๐Ÿ”ฅ ๐—™๐˜‚๐—น๐—น๐˜€๐˜๐—ฎ๐—ฐ๐—ธ ๐——๐—ฒ๐˜ƒ๐—ฒ๐—น๐—ผ๐—ฝ๐—บ๐—ฒ๐—ป๐˜ ๐—™๐—ฅ๐—˜๐—˜ ๐——๐—ฒ๐—บ๐—ผ ๐—–๐—น๐—ฎ๐˜€๐˜€ ๐—ถ๐—ป ๐—ฃ๐˜‚๐—ป๐—ฒ! ๐Ÿ˜ Want to crack a job at top tech c
๐Ÿ”ฅ ๐—™๐˜‚๐—น๐—น๐˜€๐˜๐—ฎ๐—ฐ๐—ธ ๐——๐—ฒ๐˜ƒ๐—ฒ๐—น๐—ผ๐—ฝ๐—บ๐—ฒ๐—ป๐˜ ๐—™๐—ฅ๐—˜๐—˜ ๐——๐—ฒ๐—บ๐—ผ ๐—–๐—น๐—ฎ๐˜€๐˜€ ๐—ถ๐—ป ๐—ฃ๐˜‚๐—ป๐—ฒ! ๐Ÿ˜ Want to crack a job at top tech companies? - Master Fullstack Development from the Top 1% Instructors (IITs & Top MNCs) ๐Ÿ’ก Why Join? โœ… 500+ Hiring Partners โœ… 100% Placement Assistance โœ… 60+ Hiring Drives Every Month โœ… Real-time Projects & Mentorship ๐—ฅ๐—ฒ๐—ด๐—ถ๐˜€๐˜๐—ฒ๐—ฟ ๐—ก๐—ผ๐˜„๐Ÿ‘‡ :- https://pdlink.in/3YA32zi ๐Ÿ“ข Hurry! Limited seats available.

Boost your python speed by 300% ๐Ÿ‘†
+8
Boost your python speed by 300% ๐Ÿ‘†

๐Ÿฐ ๐—™๐—ฅ๐—˜๐—˜ ๐—˜๐˜…๐—ฐ๐—ฒ๐—น ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐˜๐—ผ ๐—ž๐—ถ๐—ฐ๐—ธ๐˜€๐˜๐—ฎ๐—ฟ๐˜ ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ ๐—–๐—ฎ๐—ฟ๐—ฒ๐—ฒ๐—ฟ ๐—ถ๐—ป ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฑ
๐Ÿฐ ๐—™๐—ฅ๐—˜๐—˜ ๐—˜๐˜…๐—ฐ๐—ฒ๐—น ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐˜๐—ผ ๐—ž๐—ถ๐—ฐ๐—ธ๐˜€๐˜๐—ฎ๐—ฟ๐˜ ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ ๐—–๐—ฎ๐—ฟ๐—ฒ๐—ฒ๐—ฟ ๐—ถ๐—ป ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฑ!๐Ÿ˜ Want to master Excel for Data Analytics without spending a single rupee? ๐Ÿ’ป Here are 4 FREE resources to help you learn Excel from beginner to advanced level โ€” and land job-ready skills that recruiters love๐Ÿ‘จโ€๐Ÿ’ปโœจ๏ธ ๐‹๐ข๐ง๐ค๐Ÿ‘‡:- http://pdlink.in/4064ABS No excuses now โ€” start building your data skillset for free today!โœ…๏ธ

Most people learn SQL just enough to pull some data. But if you really understand it, you can analyze massive datasets without touching Excel or Python. Here are 8 game-changing SQL concepts that will make you a data pro: ๐Ÿ‘‡ 1. Stop pulling raw data. Start pulling insights. The biggest mistake? Running a query that gives you everything and then filtering it later. Good analysts donโ€™t pull raw data. They shape the data before it even reaches them. 2. โ€œSELECT โ€ is a rookie move. Pulling all columns is lazy and slow. A pro only selects what they need. โœ”๏ธ Fewer columns = Faster queries โœ”๏ธ Less noise = Clearer insights The more precise your query, the less time you waste cleaning data. 3. GROUP BY is your best friend. You donโ€™t need 100,000 rows of transactions. What you need is: โœ”๏ธ Sales per region โœ”๏ธ Average order size per customer โœ”๏ธ Number of signups per month Grouping turns chaotic data into useful summaries. 4. Joins = Connecting the dots. Your most important data is split across multiple tables. Want to know how much each customer spent? You need to join: โœ”๏ธ Customer info โœ”๏ธ Order history โœ”๏ธ Payments Joins = unlocking hidden insights. 5. Window functions will blow your mind. They let you: โœ”๏ธ Rank customers by total purchases โœ”๏ธ Calculate rolling averages โœ”๏ธ Compare each row to the overall trend Itโ€™s like pivot tables, but way more powerful. 6. CTEs will save you from spaghetti SQL. Instead of writing a 50-line nested query, break it into steps. CTEs (Common Table Expressions) make your SQL: โœ”๏ธ Easier to read โœ”๏ธ Easier to debug โœ”๏ธ Reusable Good SQL is clean SQL. 7. Indexes = Speed. If your queries take forever, your database is probably doing unnecessary work. Indexes help databases find data faster. If you work with large datasets, this is a game changer. SQL isnโ€™t just about pulling data. Itโ€™s about analyzing, transforming, and optimizing it. Master these 7 concepts, and youโ€™ll never look at SQL the same way again. Join us on WhatsApp: https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v

๐—Ÿ๐—ฒ๐—ฎ๐—ฟ๐—ป ๐—š๐—ฒ๐—ป๐—”๐—œ ๐—™๐—ผ๐—ฟ ๐—™๐—ฅ๐—˜๐—˜ , ๐—˜๐—ฎ๐—ฟ๐—ป ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ฒ๐˜€ & ๐— ๐—ฎ๐—ธ๐—ฒ ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐—–๐—ผ๐—น๐—น๐—ฒ๐—ด๐—ฒ ๐—œ๐—ป๐—ฑ๐—ถ๐—ฎโ€™๐˜€ ๐—”
๐—Ÿ๐—ฒ๐—ฎ๐—ฟ๐—ป ๐—š๐—ฒ๐—ป๐—”๐—œ ๐—™๐—ผ๐—ฟ ๐—™๐—ฅ๐—˜๐—˜ , ๐—˜๐—ฎ๐—ฟ๐—ป ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ฒ๐˜€ & ๐— ๐—ฎ๐—ธ๐—ฒ ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐—–๐—ผ๐—น๐—น๐—ฒ๐—ด๐—ฒ ๐—œ๐—ป๐—ฑ๐—ถ๐—ฎโ€™๐˜€ ๐—”๐—œ ๐—–๐—ต๐—ฎ๐—บ๐—ฝ๐—ถ๐—ผ๐—ป๐Ÿ˜ Join the #GreatLearningAIChallenge | ๐Ÿ—“๏ธ 13thโ€“15th July ๐ŸŽ ๐—ช๐—ต๐—ฎ๐˜ ๐—ฌ๐—ผ๐˜‚ ๐—š๐—ฒ๐˜:- โœ… Certificates worth โ‚น40,000 โ€“ Absolutely FREE โœ… Internship Opportunity at Great Learning โœ… Top 10 students from winning colleges get Third Wave Coffee vouchers โ˜• ๐Ÿ† More participants = Higher rank for your college! ๐‘๐ž๐ ๐ข๐ฌ๐ญ๐ž๐ซ ๐…๐จ๐ซ ๐…๐‘๐„๐„ ๐Ÿ‘‡:- https://pdlink.in/4ksaynS Get your classmates to join & win BIG together!๐ŸŽ“

Amazon Data Analyst Interview Questions for 1-3 years of experience role :- A. SQL: 1. You have two tables: Employee and Department. - Employee Table Columns: Employee_id, Employee_Name, Department_id, Salary - Department Table Columns: Department_id, Department_Name, Location Write an SQL query to find the name of the employee with the highest salary in each location. 2. You have two tables: Orders and Customers. - Orders Table Columns: Order_id, Customer_id, Order_Date, Amount - Customers Table Columns: Customer_id, Customer_Name, Join_Date Write an SQL query to calculate the total order amount for each customer who joined in the current year. The output should contain Customer_Name and the total amount. B. Python: 1. Basic oral questions on NumPy (e.g., array creation, slicing, broadcasting) and Matplotlib (e.g., plot types, customization). 2. Basic oral questions on pandas (like: groupby, loc/iloc, merge & join, etc.) 2. Write the code in NumPy and Pandas to replicate the functionality of your answer to the second SQL question. C. Leadership or Situational Questions: (Based on the leadership principle of Bias for Action) - Describe a situation where you had to make a quick decision with limited information. How did you proceed, and what was the outcome? (Based on the leadership principle of Dive Deep) - Can you share an example of a project where you had to delve deeply into the data to uncover insights or solve a problem? What steps did you take, and what were the results? (Based on the leadership principle of Customer Obsession) - Tell us about a time when you went above and beyond to meet a customer's needs or expectations. How did you identify their requirements, and what actions did you take to deliver exceptional service? D. Excel: Questions on advanced functions like VLOOKUP, XLookup, SUMPRODUCT, INDIRECT, TEXT functions, SUMIFS, COUNTIFS, LOOKUPS, INDEX & MATCH, AVERAGEIFS. Plus, some basic questions on pivot tables, conditional formatting, data validation, and charts. I have curated best 80+ top-notch Data Analytics Resources ๐Ÿ‘‡๐Ÿ‘‡ https://t.me/DataSimplifier Like if it helps :)

๐—›๐—ฎ๐—ฟ๐˜ƒ๐—ฎ๐—ฟ๐—ฑ ๐—๐˜‚๐˜€๐˜ ๐—ฅ๐—ฒ๐—น๐—ฒ๐—ฎ๐˜€๐—ฒ๐—ฑ ๐Ÿฑ ๐—™๐—ฅ๐—˜๐—˜ ๐—ง๐—ฒ๐—ฐ๐—ต ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐—ฌ๐—ผ๐˜‚ ๐—–๐—ฎ๐—ปโ€™๐˜ ๐— ๐—ถ๐˜€๐˜€ ๐—ถ๐—ป ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฑ!๐Ÿ˜ ๐Ÿšจ Ha
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SQL Basics for Data Analysts SQL (Structured Query Language) is used to retrieve, manipulate, and analyze data stored in databases. 1๏ธโƒฃ Understanding Databases & Tables Databases store structured data in tables. Tables contain rows (records) and columns (fields). Each column has a specific data type (INTEGER, VARCHAR, DATE, etc.). 2๏ธโƒฃ Basic SQL Commands Let's start with some fundamental queries: ๐Ÿ”น SELECT โ€“ Retrieve Data
SELECT * FROM employees; -- Fetch all columns from 'employees' table SELECT name, salary FROM employees; -- Fetch specific columns 
๐Ÿ”น WHERE โ€“ Filter Data
SELECT * FROM employees WHERE department = 'Sales'; -- Filter by department SELECT * FROM employees WHERE salary > 50000; -- Filter by salary 
๐Ÿ”น ORDER BY โ€“ Sort Data
SELECT * FROM employees ORDER BY salary DESC; -- Sort by salary (highest first) SELECT name, hire_date FROM employees ORDER BY hire_date ASC; -- Sort by hire date (oldest first) 
๐Ÿ”น LIMIT โ€“ Restrict Number of Results
SELECT * FROM employees LIMIT 5; -- Fetch only 5 rows SELECT * FROM employees WHERE department = 'HR' LIMIT 10; -- Fetch first 10 HR employees 
๐Ÿ”น DISTINCT โ€“ Remove Duplicates
SELECT DISTINCT department FROM employees; -- Show unique departments 
Mini Task for You: Try to write an SQL query to fetch the top 3 highest-paid employees from an "employees" table. You can find free SQL Resources here ๐Ÿ‘‡๐Ÿ‘‡ https://t.me/mysqldata Like this post if you want me to continue covering all the topics! ๐Ÿ‘โค๏ธ Share with credits: https://t.me/sqlspecialist Hope it helps :) #sql

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Complete SQL road map ๐Ÿ‘‡๐Ÿ‘‡ 1.Intro to SQL โ€ข Definition โ€ข Purpose โ€ข Relational DBs โ€ข DBMS 2.Basic SQL Syntax โ€ข SELECT โ€ข FROM โ€ข WHERE โ€ข ORDER BY โ€ข GROUP BY 3. Data Types โ€ข Integer โ€ข Floating-Point โ€ข Character โ€ข Date โ€ข VARCHAR โ€ข TEXT โ€ข BLOB โ€ข BOOLEAN 4.Sub languages โ€ข DML โ€ข DDL โ€ข DQL โ€ข DCL โ€ข TCL 5. Data Manipulation โ€ข INSERT โ€ข UPDATE โ€ข DELETE 6. Data Definition โ€ข CREATE โ€ข ALTER โ€ข DROP โ€ข Indexes 7.Query Filtering and Sorting โ€ข WHERE โ€ข AND โ€ข OR Conditions โ€ข Ascending โ€ข Descending 8. Data Aggregation โ€ข SUM โ€ข AVG โ€ข COUNT โ€ข MIN โ€ข MAX 9.Joins and Relationships โ€ข INNER JOIN โ€ข LEFT JOIN โ€ข RIGHT JOIN โ€ข Self-Joins โ€ข Cross Joins โ€ข FULL OUTER JOIN 10.Subqueries โ€ข Subqueries used in โ€ข Filtering data โ€ข Aggregating data โ€ข Joining tables โ€ข Correlated Subqueries 11.Views โ€ข Creating โ€ข Modifying โ€ข Dropping Views 12.Transactions โ€ข ACID Properties โ€ข COMMIT โ€ข ROLLBACK โ€ข SAVEPOINT โ€ข ROLLBACK TO SAVEPOINT 13.Stored Procedures โ€ข CREATE PROCEDURE โ€ข ALTER PROCEDURE โ€ข DROP PROCEDURE โ€ข EXECUTE PROCEDURE โ€ข User-Defined Functions (UDFs) 14.Triggers โ€ข Trigger Events โ€ข Trigger Execution and Syntax 15. Security and Permissions โ€ข CREATE USER โ€ข GRANT โ€ข REVOKE โ€ข ALTER USER โ€ข DROP USER 16.Optimizations โ€ข Indexing Strategies โ€ข Query Optimization 17.Normalization โ€ข 1NF(Normal Form) โ€ข 2NF โ€ข 3NF โ€ข BCNF 18.Backup and Recovery โ€ข Database Backups โ€ข Point-in-Time Recovery 19.NoSQL Databases โ€ข MongoDB โ€ข Cassandra etc... โ€ข Key differences 20. Data Integrity โ€ข Primary Key โ€ข Foreign Key 21.Advanced SQL Queries โ€ข Window Functions โ€ข Common Table Expressions (CTEs) 22.Full-Text Search โ€ข Full-Text Indexes โ€ข Search Optimization 23. Data Import and Export โ€ข Importing Data โ€ข Exporting Data (CSV, JSON) โ€ข Using SQL Dump Files 24.Database Design โ€ข Entity-Relationship Diagrams โ€ข Normalization Techniques 25.Advanced Indexing โ€ข Composite Indexes โ€ข Covering Indexes 26.Database Transactions โ€ข Savepoints โ€ข Nested Transactions โ€ข Two-Phase Commit Protocol 27.Performance Tuning โ€ข Query Profiling and Analysis โ€ข Query Cache Optimization ------------------ END ------------------- Some good resources to learn SQL 1.Tutorial & Courses โ€ข Learn SQL: https://bit.ly/3FxxKPz โ€ข Udacity: imp.i115008.net/AoAg7K 2. YouTube Channel's โ€ข FreeCodeCamp:rb.gy/pprz73 โ€ข Programming with Mosh: rb.gy/g62hpe 3. Books โ€ข SQL in a Nutshell: https://t.me/DataAnalystInterview/158 4. SQL Interview Questions https://t.me/sqlanalyst/72?single Join @free4unow_backup for more free resourses ENJOY LEARNING ๐Ÿ‘๐Ÿ‘

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