اکنون در دسترس! پژوهش تلگرام ۲۰۲۵ — مهمترین بینشهای سال 
Python Courses & Resources
رفتن به کانال در Telegram
Master Python with step-by-step courses – from basics to advanced projects and practical applications.
نمایش بیشتر📈 تحلیل کانال تلگرام Python Courses & Resources
کانال Python Courses & Resources (@python53) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 49 023 مشترک است و جایگاه 3 605 را در دسته آموزش و رتبه 7 936 را در منطقه الهند دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 49 023 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 04 ژوئن, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر 499 و در ۲۴ ساعت گذشته برابر 11 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 2.42% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 1.47% واکنش نسبت به کل مشترکان کسب میکند.
- دسترسی پستها: هر پست به طور میانگین 1 185 بازدید دریافت میکند. در اولین روز معمولاً 722 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 consultation, dentist, insidead, waybienad, appointment تمرکز دارد.
📝 توضیح و سیاست محتوایی
نویسنده این فضا را محل بیان دیدگاههای شخصی توصیف میکند:
“Master Python with step-by-step courses – from basics to advanced projects and practical applications.”
به لطف بهروزرسانیهای پرتکرار (آخرین داده در تاریخ 05 ژوئن, 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 آموزش تبدیل کردهاند.
49 023
مشترکین
+1124 ساعت
+1687 روز
+49930 روز
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Repost from Machine Learning with Python
Most people learn Python in random order. No wonder they feel stuck.
This roadmap fixes that.
Here are the 5 layers every data professional must master, in order:
𝟭. 𝗖𝗼𝗿𝗲 𝗣𝘆𝘁𝗵𝗼𝗻 (𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻)
Variables, loops, functions, error handling, collections.
Do not skip this. Everything else breaks without it.
𝟮. 𝗗𝗮𝘁𝗮 𝗛𝗮𝗻𝗱𝗹𝗶𝗻𝗴 & 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴
Pandas, NumPy, file handling, SQL integration, data cleaning.
This is where your actual job begins.
𝟯. 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗟𝗶𝗯𝗿𝗮𝗿𝗶𝗲𝘀
Matplotlib, Seaborn, EDA, statistical functions, hypothesis testing.
Can you turn raw data into a decision? This layer teaches you how.
𝟰. 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 & 𝗠𝗟
Scikit-Learn, clustering, feature engineering, big data tools.
This is what gets you promoted.
𝟱. 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 & 𝗕𝗲𝘀𝘁 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀
Git, virtual environments, unit testing, workflow scheduling.
This is what separates professionals from beginners.
The mistake most people make, they jump straight to ML without nailing the foundation.
You cannot build insights on broken code.
Master the layers. In order. With real data.
Save this roadmap and share it with someone who needs direction.
Where are you on this right now?
♻️ Repost to help someone learning Python the right way
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Repost from Machine Learning with Python
Follow the Machine Learning with Python channel on WhatsApp: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
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