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14 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 525 ga, so‘nggi 24 soatda esa 20 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

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𝟱 𝗙𝗥𝗘𝗘 𝗧𝗲𝗰𝗵 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗙𝗿𝗼𝗺 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁, 𝗔𝗪𝗦, 𝗜𝗕𝗠, 𝗖𝗶𝘀𝗰𝗼, 𝗮𝗻𝗱 𝗦𝘁𝗮𝗻𝗳𝗼𝗿𝗱. 😍 - Python - Artificial Intelligence, - Cybersecurity - Cloud Computing, and - Machine Learning 𝐋𝐢𝐧𝐤 👇:- https://pdlink.in/3E2wYNr Enroll For FREE & Get Certified 🎓

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I once told a hiring manager I was “proficient in SQL.” In reality, I had watched half a YouTube tutorial on 2x speed. In the interview, she said: “What’s the difference between INNER JOIN and LEFT JOIN?” I said: “It depends on your mindset.” I blacked out. She smiled. I think it was pity. Lesson? Lie if you must. But memorize the script. And never lie about tech. They will test you immediately.

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5 misconceptions about data analytics (and what's actually true): ❌ The more sophisticated the tool, the better the analyst ✅ Many analysts do their jobs with "basic" tools like Excel ❌ You're just there to crunch the numbers ✅ You need to be able to tell a story with the data ❌ You need super advanced math skills ✅ Understanding basic math and statistics is a good place to start ❌ Data is always clean and accurate ✅ Data is never clean and 100% accurate (without lots of prep work) ❌ You'll work in isolation and not talk to anyone ✅ Communication with your team and your stakeholders is essential

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𝗜𝗻𝗳𝗼𝘀𝘆𝘀 𝟭𝟬𝟬% 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍 Infosys Springboard is offering a wide range of 100% free courses with certificates to help you upskill and boost your resume—at no cost. Whether you’re a student, graduate, or working professional, this platform has something valuable for everyone. 𝐋𝐢𝐧𝐤 👇:- https://pdlink.in/4jsHZXf Enroll For FREE & Get Certified 🎓

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Microsoft Excel → Python: In Excel, you'd use =AVERAGE(TableName[ColumnName]) to find the average. In Python: TableName['ColumnName'].mean() One line. Works even if you have 10 million rows.

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Data Analyst Tech stack

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Data Structure in Python

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𝗟𝗲𝗮𝗿𝗻 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘 & 𝗘𝗹𝗲𝘃𝗮𝘁𝗲 𝗬𝗼𝘂𝗿 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱 𝗚𝗮𝗺𝗲!😍 Want to turn raw data into stunning visual stories?📊 Here are 6 FREE Power BI courses that’ll take you from beginner to pro—without spending a single rupee💰 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/4cwsGL2 Enjoy Learning ✅️

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Power BI DAX

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Repost from Python Projects & Resources

𝟰 𝗙𝗥𝗘𝗘 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍 These free, Microsoft-backed courses are a game-changer! With these resources, you’ll gain the skills and confidence needed to shine in the data analytics world—all without spending a penny. 𝐋𝐢𝐧𝐤 👇:- https://pdlink.in/4jpmI0I Enroll For FREE & Get Certified🎓

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For data analysts working with Python, mastering these top 10 concepts is essential: 1. Data Structures: Understand fundamental data structures like lists, dictionaries, tuples, and sets, as well as libraries like NumPy and Pandas for more advanced data manipulation. 2. Data Cleaning and Preprocessing: Learn techniques for cleaning and preprocessing data, including handling missing values, removing duplicates, and standardizing data formats. 3. Exploratory Data Analysis (EDA): Use libraries like Pandas, Matplotlib, and Seaborn to perform EDA, visualize data distributions, identify patterns, and explore relationships between variables. 4. Data Visualization: Master visualization libraries such as Matplotlib, Seaborn, and Plotly to create various plots and charts for effective data communication and storytelling. 5. Statistical Analysis: Gain proficiency in statistical concepts and methods for analyzing data distributions, conducting hypothesis tests, and deriving insights from data. 6. Machine Learning Basics: Familiarize yourself with machine learning algorithms and techniques for regression, classification, clustering, and dimensionality reduction using libraries like Scikit-learn. 7. Data Manipulation with Pandas: Learn advanced data manipulation techniques using Pandas, including merging, grouping, pivoting, and reshaping datasets. 8. Data Wrangling with Regular Expressions: Understand how to use regular expressions (regex) in Python to extract, clean, and manipulate text data efficiently. 9. SQL and Database Integration: Acquire basic SQL skills for querying databases directly from Python using libraries like SQLAlchemy or integrating with databases such as SQLite or MySQL. 10. Web Scraping and API Integration: Explore methods for retrieving data from websites using web scraping libraries like BeautifulSoup or interacting with APIs to access and analyze data from various sources. Give credits while sharing: https://t.me/pythonanalyst ENJOY LEARNING 👍👍

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Projects to boost your resume for data roles

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⚡️The best job today is to be a trader This year, they earned an average of $20,000 a month, working from home, traveling or in a country house. And the smartest ones are making hundreds of thousands. Do you want the same? You don't need to be a genius to make money from deals, just start reading Evelyn's channel. She explains in detail how to make $4,000 in the first week just by copying her trades, without any risks or long training. ✅Subscribe — everything you need to get started is there: @trading_evelyn

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Must-have tools for beginners: ⤷ Excel (for basics) ⤷ SQL (for querying) ⤷ Tableau/Power BI (for viz) ⤷ ChatGPT (for practice help, not copy-paste) ⤷ Kaggle (for datasets & real-world exposure) Start with these. No need for 10 certifications.

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Useful tips

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Data Projects