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Python Courses & Resources
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Master Python with step-by-step courses – from basics to advanced projects and practical applications.
Show more📈 Analytical overview of Telegram channel Python Courses & Resources
Channel Python Courses & Resources (@python53) in the English language segment is an active participant. Currently, the community unites 49 093 subscribers, ranking 3 610 in the Education category and 7 855 in the India region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 49 093 subscribers.
According to the latest data from 08 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 502 over the last 30 days and by 34 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 2.78%. Within the first 24 hours after publication, content typically collects 1.19% reactions from the total number of subscribers.
- Post reach: On average, each post receives 1 363 views. Within the first day, a publication typically gains 582 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 3.
- Thematic interests: Content is focused on key topics such as consultation, dentist, insidead, waybienad, appointment.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“Master Python with step-by-step courses – from basics to advanced projects and practical applications.”
Thanks to the high frequency of updates (latest data received on 09 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 Education category.
49 093
Subscribers
+3424 hours
+1257 days
+50230 days
Posts Archive
Repost from Machine Learning with Python
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Repost from Machine Learning with Python
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