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Data Science

Data Science

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Learn how to analyze data effectively and manage databases with ease. Buy ads: https://telega.io/c/sql_databases

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📈 Telegram kanali Data Science analitikasi

Data Science (@sql_databases) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 70 805 obunachidan iborat bo'lib, Taʼlim toifasida 2 274-o'rinni va Hindiston mintaqasida 4 582-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 70 805 obunachiga ega bo‘ldi.

25 Avgust, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -309 ga, so‘nggi 24 soatda esa -33 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 12.05% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 2.78% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 8 533 marta ko‘riladi; birinchi sutkada odatda 1 972 ta ko‘rish yig‘iladi.
  • Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 0 ta reaksiya keladi.
  • Tematik yo‘nalishlar: Kontent database, learning, linkedin, udemy, 029k| kabi asosiy mavzularga jamlangan.

📝 Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
Learn how to analyze data effectively and manage databases with ease. Buy ads: https://telega.io/c/sql_databases

Yuqori yangilanish chastotasi (oxirgi ma’lumot 26 Avgust, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Taʼlim toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.

70 805
Obunachilar
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-1127 kunlar
-30930 kunlar
Postlar arxiv
📱Data Science 📱How To Be a Lead Data Scientist

🔅 How To Be a Lead Data Scientist 📝 Build a foundation and develop skills for seasoned data scientists to level up from mod
🔅 How To Be a Lead Data Scientist 📝 Build a foundation and develop skills for seasoned data scientists to level up from model builders to AI leaders. 🌐 Author: Matthew Blasa 🔰 Level: Advanced ⏰ Duration: 1h 6m 📋 Topics: Data Science, Team Management 🔗 Join Data Science for more courses

😉 A list of the best YouTube videos To learn data science 1️⃣ SQL language ⬅️ Learning 💰 4-hour SQL course from zero to one hundred 💰 Window functions tutorial ⬅️ Projects 📎 Starting your first SQL project 💰 Data cleansing project 💰 Restaurant order analysis ⬅️ Interview 💰 How to crack the SQL interview? ➖➖➖ 2️⃣ Python ⬅️ Learning 💰 12-hour Python for Data Science course ⬅️ Projects 💰 Python project for beginners 💰 Analyzing Corona Data with Python ⬅️ Interview 💰 Python interview golden tricks 💰 Python Interview Questions ➖➖➖ 3️⃣ Statistics and machine learning ⬅️ Learning 💰 7-hour course in applied statistics 💰 Machine Learning Training Playlist ⬅️ Projects 💰 Practical ML Project ⬅️ Interview 💰 ML Interview Questions and Answers 💰 How to pass a statistics interview? ➖➖➖ 4️⃣ Product and business case studies ⬅️ Learning 💰 Building strong product understanding 💰 Product Metric Definition ⬅️ Interview 💰 Case Study Analysis Framework 💰 How to shine in a business interview?

🖥 Data Analyst Roadmap
🖥 Data Analyst Roadmap

📖 Merging and Joining Data Working with multiple datasets? Combine them just like SQL: # Inner join (default) merged = pd.me
📖 Merging and Joining Data Working with multiple datasets? Combine them just like SQL:
# Inner join (default)
merged = pd.merge(df_sales, df_customers, on='customer_id')

# Left join
pd.merge(df_sales, df_customers, on='customer_id', how='left')

# Concatenate vertically
all_data = pd.concat([df_2023, df_2024], ignore_index=True)

# Join on index
df1.join(df2, on='date')
This wraps up our Data Manipulation Using Pandas Series.

📱Data Science 📱Ethical Hacking: SQL Injection

🔅 Ethical Hacking: SQL Injection 📝 Learn about the SQL command language and SQL injections. Examine SQL injections in MySQL
🔅 Ethical Hacking: SQL Injection 📝 Learn about the SQL command language and SQL injections. Examine SQL injections in MySQL, SQL Server, and Oracle XE, and discover how attackers defeat web application firewalls. 🌐 Author: Malcolm Shore 🔰 Level: Intermediate ⏰ Duration: 1h 45m 📋 Topics: Ethical Hacking, SQL Injection 🔗 Join Data Science for more courses

SQL
+5
SQL

SQL is way easier when you actually know what matters. These are the core basics every beginner needs to build projects, answ
+5
SQL is way easier when you actually know what matters. These are the core basics every beginner needs to build projects, answer real business questions, and stop feeling overwhelmed 📊 Master these first and everything else becomes 10x easier. Save this to review later ✅

📖 SQL Learning Roadmap — 8 Key Steps: 1. Basic: Start by understanding what SQL is, why it’s used, and the different types o
📖 SQL Learning Roadmap — 8 Key Steps: 1. Basic: Start by understanding what SQL is, why it’s used, and the different types of SQL commands (DDL, DML, DCL, TCL). This builds your foundation. 2. Queries: Learn how to fetch data using commands like SELECT, FROM, WHERE, ORDER BY, and LIMIT. Practice filtering data with operators such as =, !=, LIKE, IN, and BETWEEN. 3. Joins: To work with multiple tables, you must understand INNER, LEFT, RIGHT, and FULL OUTER JOIN. Know how primary and foreign keys relate tables. 4. Functions: Use built-in functions like COUNT, SUM, AVG, MIN, and MAX for data analysis. Learn how to group data using GROUP BY and filter groups with HAVING. 5. Subqueries: Write queries within queries! Learn scalar, correlated, and multi-row subqueries. They’re powerful for solving complex data problems. 6. Data Manipulation: Master how to change data using INSERT, UPDATE, and DELETE. Also, understand transactions using BEGIN, COMMIT, and ROLLBACK to maintain data integrity. 7. Advanced: Take it further with window functions (ROW_NUMBER, RANK, LEAD, LAG), CTEs (WITH), views, and indexing to write efficient and optimized queries. 8. Practice: The final step is consistent practice. Work with real-world datasets, focus on query optimization, and solve challenges on platforms like LeetCode, Mode, or HackerRank.

📖 4 Main in Database Types
📖 4 Main in Database Types

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📱Data Science 📱The 80/20 Rule of Data Science

🔅 The 80/20 Rule of Data Science 📝 Explore the core concepts of the 80/20 rule for data science and how to get most of the
🔅 The 80/20 Rule of Data Science 📝 Explore the core concepts of the 80/20 rule for data science and how to get most of the value with minimal effort. 🌐 Author: Howard Friedman 🔰 Level: Intermediate ⏰ Duration: 1h 26m 📋 Topics: Data Science, Project Engineering, Team Management 🔗 Join Data Science for more courses

📖 Data Visualisation CheatSheet
📖 Data Visualisation CheatSheet

📖 Data Analyst
📖 Data Analyst

📖 MOST COMMON SQL INTERVIEW QUESTION Do you knew this? 👉 “What is the order of execution in an SQL query?” Don’t let the SE
📖 MOST COMMON SQL INTERVIEW QUESTION Do you knew this? 👉 “What is the order of execution in an SQL query?” Don’t let the SELECT fool you – it’s NOT the first step! 😮 Here’s the correct order that SQL follows behind the scenes: 🔢 SQL Order of Execution: 1️⃣ FROM 2️⃣ JOIN 3️⃣ WHERE 4️⃣ GROUP BY 5️⃣ HAVING 6️⃣ SELECT 7️⃣ DISTINCT 8️⃣ ORDER BY 9️⃣ LIMIT / OFFSET 🔥 Pro tip: Interviewers LOVE this question to test your SQL fundamentals! Memorize it, understand it – and impress in your next interview. 💼

📦 Exercise Files

📱Data Science 📱PostgreSQL Essential Training

🔅 PostgreSQL Essential Training 📝 Learn how to set up and work with one of the worlds most popular open-source database pla
🔅 PostgreSQL Essential Training 📝 Learn how to set up and work with one of the worlds most popular open-source database platforms, PostgreSQL. 🌐 Author: Adam Wilbert 🔰 Level: Intermediate ⏰ Duration: 3h 18m 📋 Topics: PostgreSQL 🔗 Join Data Science for more courses