Learn Python Coding
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Learn Python through simple, practical examples and real coding ideas. Clear explanations, useful snippets, and hands-on learning for anyone starting or improving their programming skills.

Admin: @HusseinSheikho || @Hussein_Sheikho
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πŸš€ Master Data Science & Programming!

Unlock your potential with this curated list of Telegram channels. Whether you need books, datasets, interview prep, or project ideas, we have the perfect resource for you. Join the community today!


πŸ”° Machine Learning with Python
Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.
https://t.me/CodeProgrammer

πŸ”– Machine Learning
Machine learning insights, practical tutorials, and clear explanations for beginners and aspiring data scientists. Follow the channel for models, algorithms, coding guides, and real-world ML applications.
https://t.me/DataScienceM

🧠 Code With Python
This channel delivers clear, practical content for developers, covering Python, Django, Data Structures, Algorithms, and DSA – perfect for learning, coding, and mastering key programming skills.
https://t.me/DataScience4

🎯 PyData Careers | Quiz
Python Data Science jobs, interview tips, and career insights for aspiring professionals.
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πŸ’Ύ Kaggle Data Hub
Your go-to hub for Kaggle datasets – explore, analyze, and leverage data for Machine Learning and Data Science projects.
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Advancing research in Machine Learning – practical insights, tools, and techniques for researchers.
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πŸ’¬ Data Science Chat
An active community group for discussing data challenges and networking with peers.
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🐍 Python Arab| Ψ¨Ψ§ΩŠΨ«ΩˆΩ† عربي
The largest Arabic-speaking group for Python developers to share knowledge and help.
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πŸ–Š Data Science Jupyter Notebooks
Explore the world of Data Science through Jupyter Notebooksβ€”insights, tutorials, and tools to boost your data journey. Code, analyze, and visualize smarter with every post.
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✨ compileall | Python Standard Library ✨

πŸ“– Provides utilities for byte-compiling Python source files into bytecode across a directory tree, a single file, or all locations on sys.path.

🏷️ #Python
✨ Quiz: For Loops in Python (Definite Iteration) ✨

πŸ“– Test your understanding of Python loops, iterables, and control flow with break, continue, and StopIteration.

🏷️ #basics #python
✨ copyreg | Python Standard Library ✨

πŸ“– Provides a registry for defining custom pickling and copying functions for specific object types.

🏷️ #Python
✨ Quiz: Building a Python GUI Application With Tkinter ✨

πŸ“– Test your Tkinter skills with this interactive challenge on widgets, layouts, event loops, and text/file handling in Python GUIs.

🏷️ #basics #gui #stdlib
✨ Quiz: Using Loguru to Simplify Python Logging ✨

πŸ“– Test your knowledge of Loguru for Python logging, from zero-config setup and log levels to custom formats and adding context.

🏷️ #intermediate #tools
πŸš€ Sber has released two open-source MoE models: GigaChat-3.1 Ultra and Lightning

Both code and weights are available under the MIT license on HuggingFace.

πŸ‘‰ Key details:

β€’ Trained from scratch (not a finetune) on proprietary data and infrastructure
β€’ Mixture-of-Experts (MoE) architecture

Models:

🧠 GigaChat-3.1 Ultra
β€’ 702B MoE model for high-performance environments
β€’ Outperforms DeepSeek-V3-0324 and Qwen3-235B on math and reasoning benchmarks
β€’ Supports FP8 training and MTP

⚑️ GigaChat-3.1 Lightning
β€’ 10B model (1.8B active parameters)
β€’ Outperforms Qwen3-4B and Gemma-3-4B on Sber benchmarks
β€’ Efficient local inference
β€’ Up to 256k context

Engineering highlights:

β€’ Custom metric to detect and reduce generation loops
β€’ DPO training moved to native FP8
β€’ Improvements in post-training pipeline
β€’ Identified and fixed a critical issue affecting evaluation quality

🌍 Trained on 14 languages (optimized for English and Russian)

Use cases:

β€’ chatbots
β€’ AI assistants
β€’ copilots
β€’ internal ML systems

Sber provides a solid open foundation for developers to build production-ready AI systems with lower infrastructure costs.
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✨ Quiz: Implementing the Factory Method Pattern in Python ✨

πŸ“– Learn how the Factory Method pattern separates creation from use, promotes decoupling, and organizes Python products efficiently.

🏷️ #intermediate #best-practices
✨ Dictionaries in Python ✨

πŸ“– Learn how dictionaries in Python work: create and modify key-value pairs using dict literals, the dict() constructor, built-in methods, and operators.

🏷️ #basics #python
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✨ ctypes | Python Standard Library ✨

πŸ“– Allows for calling functions in shared C libraries and DLLs using C-compatible data types.

🏷️ #Python
✨ Quiz: Reading Input and Writing Output in Python ✨

πŸ“– Test your Python basics: read user input with input(), display output with print(), and handle numeric conversions.

🏷️ #basics #python
This channels is for Programmers, Coders, Software Engineers.

0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages

βœ… https://t.me/addlist/8_rRW2scgfRhOTc0

βœ… https://t.me/Codeprogrammer
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✨ curses | Python Standard Library ✨

πŸ“– Provides tools for building text-based user interfaces in Unix terminals, providing control over cursor position, colors, windows, and keyboard input.

🏷️ #Python
✨ Quiz: Exploring Protocols in Python ✨

πŸ“– Test your knowledge of Python protocols, structural subtyping, and static type checking, including generic and subprotocol usage.

🏷️ #intermediate #python
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✨ dbm | Python Standard Library ✨

πŸ“– Provides a generic dictionary-like interface to DBM-style key-value databases backed by a file on disk.

🏷️ #Python
✨ Quiz: Python Continuous Integration and Deployment Using GitHub Actions ✨

πŸ“– Practice essential GitHub Actions concepts, from workflow file locations to triggers and common CI/CD tasks, with this hands-on quiz.

🏷️ #advanced #devops
✨ Quiz: Gemini CLI vs Claude Code: Which to Choose for Python Tasks ✨

πŸ“– Compare Gemini CLI and Claude Code across user experience, performance, code quality, and cost to find the right AI coding tool for you.

🏷️ #intermediate #ai #tools
πŸ‘©β€πŸ’» Core Python data structures

https://t.me/DataScience4 βœ…
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