Python Interviews

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Join this channel to learn python for web development, data science, artificial intelligence and machine learning with quizzes, projects and amazing resources for free For collaborations: @coderfun

Network:Free Courses with Certificate - Python Programming, Data Science, Java Coding, SQL, Web Development, AI, ML, ChatGPT Expert India14 423 Technologies & Applications4 609...

📈 Analytical overview of Telegram channel Python Interviews

Channel Python Interviews (@pythoninterviews) in the English language segment is an active participant. Currently, the community unites 28 837 subscribers, ranking 4 609 in the Technologies & Applications category and 14 423 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 28 837 subscribers.

According to the latest data from 27 July, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 96 over the last 30 days and by 11 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 2.48%. Within the first 24 hours after publication, content typically collects 0.57% reactions from the total number of subscribers.
Post reach: On average, each post receives 715 views. Within the first day, a publication typically gains 163 views.
Reactions and interaction: The audience actively supports content: the average number of reactions per post is 2.
Thematic interests: Content is focused on key topics such as |--, link:-, learning, sql, analytic.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
“Join this channel to learn python for web development, data science, artificial intelligence and machine learning with quizzes, projects and amazing resources for free For collaborations: @coderfun”

Thanks to the high frequency of updates (latest data received on 28 July, 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.

28 837

Subscribers

+1124 hours

+447 days

+9630 days

715

Post views

~ 16324 hours

~ 22448 hours

2.48%

Engagement rate

No data

Posts per day

Ads index

beta

Posts Archive

28 837

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Practical Python Data Visualization Автор: Ashwin Pajankar

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28 837

Feature Engineering: The Hidden Skill That Makes or Breaks ML Models Most people chase better algorithms. Professionals chase better features. Because no matter how fancy your model is, if the data doesn’t speak the right language. it won’t learn anything meaningful. 🔍 So What Exactly Is Feature Engineering? It’s not just cleaning data. It’s translating raw, messy reality into something your model can understand. You’re basically asking:

“How can I represent the real world in numbers, without losing its meaning?”

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Feature engineering isn’t preprocessing. It’s the art of teaching your model how to understand the world.

28 837

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28 837

✅8-Week Beginner Roadmap to Learn Data Analysis 📊 🗓️ Week 1: Excel & Data Basics Goal: Master data organization and analysis basics Topics: Excel formulas, functions, PivotTables, data cleaning Tools: Microsoft Excel, Google Sheets Mini Project: Analyze sales or survey data with PivotTables 🗓️ Week 2: SQL Fundamentals Goal: Learn to query databases efficiently Topics: SELECT, WHERE, JOIN, GROUP BY, subqueries Tools: MySQL, PostgreSQL, SQLite Mini Project: Query sample customer or sales database 🗓️ Week 3: Data Visualization Basics Goal: Create meaningful charts and graphs Topics: Bar charts, line charts, scatter plots, dashboards Tools: Tableau, Power BI, Excel charts Mini Project: Build dashboard to analyze sales trends 🗓️ Week 4: Data Cleaning & Preparation Goal: Handle messy data for analysis Topics: Handling missing values, duplicates, data types Tools: Excel, Python (Pandas) basics Mini Project: Clean and prepare real-world dataset for analysis 🗓️ Week 5: Statistics for Data Analysis Goal: Understand key statistical concepts Topics: Descriptive stats, distributions, correlation, hypothesis testing Tools: Excel, Python (SciPy, NumPy) Mini Project: Analyze survey data & draw insights 🗓️ Week 6: Advanced SQL & Database Concepts Goal: Optimize queries & explore database design basics Topics: Window functions, indexes, normalization Tools: SQL Server, MySQL Mini Project: Complex query for sales and customer analysis 🗓️ Week 7: Automating Analysis with Python Goal: Use Python for repetitive data tasks Topics: Pandas automation, data aggregation, visualization scripting Tools: Jupyter Notebook, Pandas, Matplotlib Mini Project: Automate monthly sales report generation 🗓️ Week 8: Capstone Project + Reporting Goal: End-to-end analysis and presentation Project Ideas: Customer segmentation, sales forecasting, churn analysis Tools: Tableau/Power BI for visualization + Python/SQL for backend Bonus: Present findings in a polished report or dashboard 💡 Tips: ⦁ Practice querying and analysis on public datasets (Kaggle, data.gov) ⦁ Join data challenges and community projects 💬 Tap ❤️ for the detailed explanation of each topic!

28 837

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