Python Projects & Free Books
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شبکه:📈 تحلیل کانال تلگرام Python Projects & Free Books
کانال Python Projects & Free Books (@pythonfreebootcamp) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 40 659 مشترک است و جایگاه 3 224 را در دسته فناوری و برنامه‌ها و رتبه 9 418 را در منطقه الهند دارد.
📊 شاخص‌های مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 40 659 مشترک جذب کرده است.
بر اساس آخرین داده‌ها در تاریخ 05 اکتبر, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر -135 و در ۲۴ ساعت گذشته برابر -12 بوده و همچنان دسترسی گسترده‌ای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 3.58% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 0.78% واکنش نسبت به کل مشترکان کسب می‌کند.
- دسترسی پست‌ها: هر پست به طور میانگین 1 455 بازدید دریافت می‌کند. در اولین روز معمولاً 316 بازدید جمع‌آوری می‌شود.
- واکنش‌ها و تعامل: مخاطبان به‌طور فعال حمایت می‌کنند؛ میانگین واکنش به هر پست 3 است.
- علایق موضوعی: محتوا بر موضوعات کلیدی مانند learning, analyst, framework, link:-, structure تمرکز دارد.
📝 توضیح و سیاست محتوایی
نویسنده این فضا را محل بیان دیدگاه‌های شخصی توصیف می‌کند:
“Python Interview Projects & Free Courses
Admin: @Coderfun”
به لطف به‌روزرسانی‌های پرتکرار (آخرین داده در تاریخ 06 اکتبر, 2026)، کانال همواره به‌روز و دارای دسترسی بالاست. تحلیل‌ها نشان می‌دهد مخاطبان به‌طور فعال با محتوا تعامل دارند و آن را به نقطه اثرگذاری مهم در دسته فناوری و برنامه‌ها تبدیل کرده‌اند.
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پست‌های کانال
| 2 |  🎯 GigaChat 3.5 Reasoning: 5 Key Features
1️⃣ Advanced Reasoning: Explores multiple step-by-step paths, using automated verification to reinforce correct answers and self-correct
2️⃣ Autonomous Tool Usage: Independently decides when to call external APIs or revise earlier steps
3️⃣ Linear Attention: Proprietary architecture retains key context points without re-matching from scratch
4️⃣ Token Economy: Uses 37% fewer tokens than DeepSeek V4 Flash Preview on math problems
5️⃣ Proven Performance: Open-source LLM (built on GigaChat 3.5 Ultra) with massive benchmark gains:
• IFBench: 44 → 77
• Natural Plan: 64 → 80
• LiveCodeBench v6: 56 → 85
🔗 MIT License. Weights on Hugging Face: fp8 | bf16 | 1 188 |
| 3 | Let’s dive into our first mini project using Python:
Project 1: Number Guessing Game 🎯
Goal:
The computer randomly picks a number between 1 and 100.
The user has to guess it — and the program gives hints like “Too High” or “Too Low” until the user gets it right.
Code:
import random
number_to_guess = random.randint(1, 100)
guess = None
attempts = 0
print("Welcome to the Number Guessing Game!")
print("I'm thinking of a number between 1 and 100.")
while guess != number_to_guess:
guess = int(input("Enter your guess: "))
attempts += 1
if guess < number_to_guess:
print("Too low! Try again.")
elif guess > number_to_guess:
print("Too high! Try again.")
else:
print(f"Congratulations! You guessed it in {attempts} tries.")
Concepts used:
• random.randint() for generating numbers
• Taking user input using input() & converting input to integers
• Using while loops and if-else logic
React with ♥️ for the next project
Important Python Concepts: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L/1441
For all resources and cheat sheets, check out our Telegram channel
👇👇
https://t.me/pythonproz
Hope it helps :) | 1 481 |
| 4 | Learn AI for Free in 2026👇
1/ Kaggle Learn:
https://www.kaggle.com/learn
2/ Anthropic Learn:
https://www.anthropic.com/learn
3/ OpenAI Academy:
https://academy.openai.com/
4/ Google AI:
https://grow.google/ai/
5/ LangChain Academy:
https://academy.langchain.com/ | 1 696 |
| 5 | Roadmap to become a data analyst
1. Foundation Skills:
•Strengthen Mathematics: Focus on statistics relevant to data analysis.
•Excel Basics: Master fundamental Excel functions and formulas.
2. SQL Proficiency:
•Learn SQL Basics: Understand SELECT statements, JOINs, and filtering.
•Practice Database Queries: Work with databases to retrieve and manipulate data.
3. Excel Advanced Techniques:
•Data Cleaning in Excel: Learn to handle missing data and outliers.
•PivotTables and PivotCharts: Master these powerful tools for data summarization.
4. Data Visualization with Excel:
•Create Visualizations: Learn to build charts and graphs in Excel.
•Dashboard Creation: Understand how to design effective dashboards.
5. Power BI Introduction:
•Install and Explore Power BI: Familiarize yourself with the interface.
•Import Data: Learn to import and transform data using Power BI.
6. Power BI Data Modeling:
•Relationships: Understand and establish relationships between tables.
•DAX (Data Analysis Expressions): Learn the basics of DAX for calculations.
7. Advanced Power BI Features:
•Advanced Visualizations: Explore complex visualizations in Power BI.
•Custom Measures and Columns: Utilize DAX for customized data calculations.
8. Integration of Excel, SQL, and Power BI:
•Importing Data from SQL to Power BI: Practice connecting and importing data.
•Excel and Power BI Integration: Learn how to use Excel data in Power BI.
9. Business Intelligence Best Practices:
•Data Storytelling: Develop skills in presenting insights effectively.
•Performance Optimization: Optimize reports and dashboards for efficiency.
10. Build a Portfolio:
•Showcase Excel Projects: Highlight your data analysis skills using Excel.
•Power BI Projects: Feature Power BI dashboards and reports in your portfolio.
11. Continuous Learning and Certification:
•Stay Updated: Keep track of new features in Excel, SQL, and Power BI.
•Consider Certifications: Obtain relevant certifications to validate your skills. | 1 725 |
| 6 | 🐍 Python Roadmap
1️⃣ Basics: 📝📜 Syntax, Variables, Data Types
2️⃣ Control Flow: 🔄🤖 If-Else, Loops, Functions
3️⃣ Data Structures: 🗂️🔢 Lists, Tuples, Dictionaries, Sets
4️⃣ OOP in Python: 📦🎭 Classes, Inheritance, Decorators
5️⃣ File Handling: 📄📂 Read/Write, JSON, CSV
6️⃣ Modules & Libraries: 📦🚀 NumPy, Pandas, Matplotlib
7️⃣ Web Development: 🌍🔧 Flask, Django, FastAPI
8️⃣ Automation & Scripting: 🤖🛠️ Web Scraping, Selenium, Bash Scripting
9️⃣ Machine Learning: 🧠📈 TensorFlow, Scikit-learn, PyTorch
🔟 Projects & Practice: 📂🎯 Create apps, scripts, and contribute to open source
React ❤️ for more | 1 827 |
| 7 |  🔰 Comprehensions in python with example | 2 089 |
| 8 |  If you’re a student, graduate, or someone looking for a career switch, read this.
Most people spend months watching random YouTube videos and still don’t become job-ready.
Instead, learn in a structured offline classroom.
📌 Data Analytics with GenAI
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Seats are limited.
👉 Register Here: https://lp.pwskills.com/data-analytics-course-offline-batch0?utm_source=telegram&utm_medium=influencer&utm_campaign=daoffline | 1 855 |
| 9 | ✅ Complete Roadmap to Learn Python Programming 🐍💻
Week 1: Python Basics
• Install Python and VS Code
• Learn variables, data types, input, output
• Practice arithmetic and string operations
• Write 10 small programs
Example: Calculator, temperature converter
Week 2: Control Flow
• Learn if, else, elif
• Learn for and while loops
• Use break and continue
• Solve 20 logic problems
Example: Number guessing game
Week 3: Data Structures
• Lists, tuples, sets, dictionaries
• Indexing, slicing, methods
• Loop through collections
• Solve real problems
Example: Student marks analysis
Week 4: Functions and Modules
• Define functions
• Use parameters and return values
• Learn lambda functions
• Import built-in modules
Example: Reusable math utility
Week 5: Strings and File Handling
• String methods and formatting
• Read and write files
• Handle CSV and text files
• Build small file-based programs
Example: Log file analyzer
Week 6: Error Handling and Debugging
• Learn try, except, finally
• Understand common errors
• Use print and debugger
• Fix broken programs
Example: Robust input validator
Week 7: Object-Oriented Programming
• Classes and objects
• Constructors and methods
• Inheritance and encapsulation
• Build simple class-based apps
Example: Bank account system
Week 8: Standard Libraries
• datetime, math, random
• os and sys basics
• Work with JSON
• Write utility scripts
Example: Automated folder organizer
Week 9: Working with External Packages
• Learn pip and virtual environments
• Use requests library
• Basic API calls
• Handle API responses
Example: Weather app using API
Week 10: Data Handling Basics
• Intro to NumPy
• Intro to Pandas
• Read CSV and Excel files
• Basic data cleaning
Example: Sales data summary
Week 11: Mini Projects
• Build 2 small projects
• Focus on logic and structure
• Write clean, readable code
Examples:
• To-do list app
• Expense tracker
Week 12: Final Project and Revision
• Build one end-to-end project
• Revise core concepts
• Practice interview-style questions
Example projects:
• Simple automation tool
• Data analysis mini project
Daily Rule for You:
• Code at least 60 minutes
• Solve 5 problems daily
• Rewrite old code weekly
Double Tap ♥️ For Detailed Explanation | 1 475 |
| 10 | 🔰 Comprehensions in python with example | 1 482 |
| 11 |  Aaj hi ek certified Hackar bano!💻
Shuru se saari cheeze seekho bilkul basic se!!
PW skills leke aaya h certified Ethical Hacking ka course!!
Isme milega :
✅ Hands on Practice
✅ LIVE Hacking Labs
✅ Certificate after Completion
Sirf Rs 4999 mai
Abhi enroll karo *HACK30* Coupon code use karke 30% OFF milega!
Enroll NOW : https://pwskills.com/web-development/certified-ethical-hacking-course-035473/?source=pwskills.com&position=course_dropdown&from=home_page&utm_source=pwskills&utm_medium=telegram&utm_campaign=ethical_hacking | 1 634 |
| 12 | Here are some tricky🧩 SQL interview questions!
1. Find the second-highest salary in a table without using LIMIT or TOP.
2. Write a SQL query to find all employees who earn more than their managers.
3. Find the duplicate rows in a table without using GROUP BY.
4. Write a SQL query to find the top 10% of earners in a table.
5. Find the cumulative sum of a column in a table.
6. Write a SQL query to find all employees who have never taken a leave.
7. Find the difference between the current row and the next row in a table.
8. Write a SQL query to find all departments with more than one employee.
9. Find the maximum value of a column for each group without using GROUP BY.
10. Write a SQL query to find all employees who have taken more than 3 leaves in a month.
These questions are designed to test your SQL skills, including your ability to write efficient queries, think creatively, and solve complex problems.
Here are the answers to these questions:
1. SELECT MAX(salary) FROM table WHERE salary NOT IN (SELECT MAX(salary) FROM table)
2. SELECT e1.* FROM employees e1 JOIN employees e2 ON e1.manager_id = (link unavailable) WHERE e1.salary > e2.salary
3. SELECT * FROM table WHERE rowid IN (SELECT rowid FROM table GROUP BY column HAVING COUNT(*) > 1)
4. SELECT * FROM table WHERE salary > (SELECT PERCENTILE_CONT(0.9) WITHIN GROUP (ORDER BY salary) FROM table)
5. SELECT column, SUM(column) OVER (ORDER BY rowid) FROM table
6. SELECT * FROM employees WHERE id NOT IN (SELECT employee_id FROM leaves)
7. SELECT *, column - LEAD(column) OVER (ORDER BY rowid) FROM table
8. SELECT department FROM employees GROUP BY department HAVING COUNT(*) > 1
9. SELECT MAX(column) FROM table WHERE column NOT IN (SELECT MAX(column) FROM table GROUP BY group_column)
Here you can find essential SQL Interview Resources👇
https://t.me/mysqldata
Like this post if you need more 👍❤️
Hope it helps :) | 1 900 |
| 13 |  📊 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 🚀
✅ 100% FREE learning opportunities
✅ Great for students, freshers, and beginners
✅ Help you build a stronger resume with recognized names like Cisco, Google, and Microsoft
✅ Useful for analytics internships, off-campus drives, and fresher hiring
🔗 𝗘𝗻𝗿𝗼𝗹𝗹 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘👇:
https://pdlink.in/4eRA6eF
🚀 Start learning today. Build your analytics foundation. Earn free certifications. Move one step closer to your Data Analyst career. | 1 566 |
| 14 |  15 Best Project Ideas for Python : 🐍
🚀 Beginner Level:
1. Simple Calculator
2. To-Do List
3. Number Guessing Game
4. Dice Rolling Simulator
5. Word Counter
🌟 Intermediate Level:
6. Weather App
7. URL Shortener
8. Movie Recommender System
9. Chatbot
10. Image Caption Generator
🌌 Advanced Level:
11. Stock Market Analysis
12. Autonomous Drone Control
13. Music Genre Classification
14. Real-Time Object Detection
15. Natural Language Processing (NLP) Sentiment Analysis | 1 643 |
| 15 | 7 GitHub repos to master AI engineering in 2026 👇
1/ Awesome Artificial Intelligence:
https://github.com/owainlewis/awesome-artificial-intelligence
2/ Awesome LLM Apps:
https://github.com/Shubhamsaboo/awesome-llm-apps
3/ 100 Days of ML Code:
https://github.com/avik-jain/100-Days-of-ML-Code
4/ System Prompts and AI Tools:
https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools
5/ AI Agents for Beginners:
https://github.com/microsoft/ai-agents-for-beginners
6/ Microsoft Gen AI for Beginners:
https://github.com/microsoft/ai-for-beginners
7/ Learn Agentic AI:
https://github.com/panaversity/learn-agentic-ai | 1 859 |
| 16 | 🐍 𝐏𝐲𝐭𝐡𝐨𝐧 𝐟𝐞𝐥𝐭 𝐢𝐦𝐩𝐨𝐬𝐬𝐢𝐛𝐥𝐞 𝐚𝐭 𝐟𝐢𝐫𝐬𝐭, 𝐛𝐮𝐭 𝐭𝐡𝐞𝐬𝐞 𝟗 𝐬𝐭𝐞𝐩𝐬 𝐜𝐡𝐚𝐧𝐠𝐞𝐝 𝐞𝐯𝐞𝐫𝐲𝐭𝐡𝐢𝐧𝐠!
.
.
1️⃣ 𝐌𝐚𝐬𝐭𝐞𝐫𝐞𝐝 𝐭𝐡𝐞 𝐁𝐚𝐬𝐢𝐜𝐬: Started with foundational Python concepts like variables, loops, functions, and conditional statements.
2️⃣ 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐞𝐝 𝐄𝐚𝐬𝐲 𝐏𝐫𝐨𝐛𝐥𝐞𝐦𝐬: Focused on beginner-friendly problems on platforms like LeetCode and HackerRank to build confidence.
3️⃣ 𝐅𝐨𝐥𝐥𝐨𝐰𝐞𝐝 𝐏𝐲𝐭𝐡𝐨𝐧-𝐒𝐩𝐞𝐜𝐢𝐟𝐢𝐜 𝐏𝐚𝐭𝐭𝐞𝐫𝐧𝐬: Studied essential problem-solving techniques for Python, like list comprehensions, dictionary manipulations, and lambda functions.
4️⃣ 𝐋𝐞𝐚𝐫𝐧𝐞𝐝 𝐊𝐞𝐲 𝐋𝐢𝐛𝐫𝐚𝐫𝐢𝐞𝐬: Explored popular libraries like Pandas, NumPy, and Matplotlib for data manipulation, analysis, and visualization.
5️⃣ 𝐅𝐨𝐜𝐮𝐬𝐞𝐝 𝐨𝐧 𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐬: Built small projects like a to-do app, calculator, or data visualization dashboard to apply concepts.
6️⃣ 𝐖𝐚𝐭𝐜𝐡𝐞𝐝 𝐓𝐮𝐭𝐨𝐫𝐢𝐚𝐥𝐬: Followed creators like CodeWithHarry and Shradha Khapra for in-depth Python tutorials.
7️⃣ 𝐃𝐞𝐛𝐮𝐠𝐠𝐞𝐝 𝐑𝐞𝐠𝐮𝐥𝐚𝐫𝐥𝐲: Made it a habit to debug and analyze code to understand errors and optimize solutions.
8️⃣ 𝐉𝐨𝐢𝐧𝐞𝐝 𝐌𝐨𝐜𝐤 𝐂𝐨𝐝𝐢𝐧𝐠 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬: Participated in coding challenges to simulate real-world problem-solving scenarios.
9️⃣ 𝐒𝐭𝐚𝐲𝐞𝐝 𝐂𝐨𝐧𝐬𝐢𝐬𝐭𝐞𝐧𝐭: Practiced daily, worked on diverse problems, and never skipped Python for more than a day.
I have curated the best interview resources to crack Python Interviews 👇👇
https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L
Hope you'll like it
Like this post if you need more resources like this 👍❤️
#Python | 2 029 |
| 17 |  🔰 Python functions | 2 145 |
| 18 |  If you work with Python, remember a simple rule: do not modify a list while iterating over it. 🐍🛑 This can lead to unexpected results because the iterator does not track structural changes.
Here is an example that looks logical but works incorrectly: 🤔
items = [1, 2, 2, 3, 4]
for item in items:
if item == 2:
items.remove(item)
print(items)
# Output: [1, 2, 3, 4]
It seems that all 2s should disappear, but one remains. ❓ Why?
After removing an element, the list shifts, but the loop moves on — as a result, some values are simply skipped. 🔄🚫
How to do it correctly — iterate over a copy: ✅
for item in items[:]:
if item == 2:
items.remove(item)
print(items)
# Output: [1, 3, 4]
Even better — use list comprehension: 🚀
items = [x for x in items if x != 2]
Conclusion: 🏁 do not modify a collection during iteration. This can lead to skipped elements, duplication, or even errors during execution. 🛠️🚧
#Python #Coding #Programming #Debugging #TechTips #PythonTips | 2 298 |
| 19 |  Python Basics Arrays & Loops 🐍
Essential you need to start strong 💪
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ENJOY LEARNING 👍👍 | 2 674 |
