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Learn Python Coding

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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πŸ“ˆ Analytical overview of Telegram channel Learn Python Coding

Channel Learn Python Coding (@pythonre) in the English language segment is an active participant. Currently, the community unites 39 165 subscribers, ranking 3 501 in the Technologies & Applications category and 10 515 in the India region.

πŸ“Š Audience metrics and dynamics

Since its creation on Π½Π΅Π²Ρ–Π΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 39 165 subscribers.

According to the latest data from 09 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 443 over the last 30 days and by 15 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 2.52%. Within the first 24 hours after publication, content typically collects 0.96% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 988 views. Within the first day, a publication typically gains 374 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 4.
  • Thematic interests: Content is focused on key topics such as math, harvard, oxford, supervision, waybienad.

πŸ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
β€œLearn 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”

Thanks to the high frequency of updates (latest data received on 10 June, 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.

39 165
Subscribers
+1524 hours
+827 days
+44330 days
Posts Archive
✨ parameter | AI Coding Glossary ✨ πŸ“– A learned internal value of a model, such as a weight or bias. 🏷️ #Python

✨ convolutional network | AI Coding Glossary ✨ πŸ“– A neural network that uses local receptive fields and shared weights to process structured signals such as images. 🏷️ #Python

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Python Notes 🌟🌟🌟🌟🌟 #python https://t.me/addlist/8_rRW2scgfRhOTc0 ⚑️

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✨ Quiz: What Can I Do With Python? ✨ πŸ“– Test your knowledge of what Python can and can't do, from web and GUI apps to data sc
✨ Quiz: What Can I Do With Python? ✨ πŸ“– Test your knowledge of what Python can and can't do, from web and GUI apps to data science, CLI tools, and embedded systems. 🏷️ #basics #career

✨ loss function | AI Coding Glossary ✨ πŸ“– A scalar objective that measures prediction error and shapes gradients to guide model training. 🏷️ #Python

✨ reinforcement learning | AI Coding Glossary ✨ πŸ“– A learning approach where an agent improves decisions by interacting with an environment and maximizing cumulative reward. 🏷️ #Python

✨ What Can I Do With Python? ✨ πŸ“– Learn how Python builds software, powers AI, automates tasks, and drives robotics. Discover
✨ What Can I Do With Python? ✨ πŸ“– Learn how Python builds software, powers AI, automates tasks, and drives robotics. Discover tools and projects to guide your programming journey. 🏷️ #basics #career

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✨ When Should You Use .__repr__() vs .__str__() in Python? ✨ πŸ“– Find out when to choose Python's __repr__() vs __str__() in y
✨ When Should You Use .__repr__() vs .__str__() in Python? ✨ πŸ“– Find out when to choose Python's __repr__() vs __str__() in your classes so your objects show helpful information for debugging and user output. 🏷️ #intermediate #best-practices

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✨ token | AI Coding Glossary ✨ πŸ“– A minimal unit of text used by NLP systems and language models. 🏷️ #Python

✨ context window | AI Coding Glossary ✨ πŸ“– The maximum span of tokens that a language model can consider at once. 🏷️ #Python

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