Python Courses & Resources

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Master Python with step-by-step courses – from basics to advanced projects and practical applications.

Ko'proq ko'rsatish

Tarmoq:Machine Learning with Python Hindiston7 855 Taʼlim3 610...

📈 Telegram kanali Python Courses & Resources analitikasi

Python Courses & Resources (@python53) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 49 093 obunachidan iborat bo'lib, Taʼlim toifasida 3 610-o'rinni va Hindiston mintaqasida 7 855-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 49 093 obunachiga ega bo‘ldi.

08 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 502 ga, so‘nggi 24 soatda esa 34 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

Tasdiqlash holati: Tasdiqlanmagan
Jalb etish (ER): Auditoriya o‘rtacha 2.78% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.19% ini tashkil etuvchi reaksiyalarni to‘playdi.
Post qamrovi: Har bir post o‘rtacha 1 363 marta ko‘riladi; birinchi sutkada odatda 582 ta ko‘rish yig‘iladi.
Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 3 ta reaksiya keladi.
Tematik yo‘nalishlar: Kontent consultation, dentist, insidead, waybienad, appointment kabi asosiy mavzularga jamlangan.

📝 Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“Master Python with step-by-step courses – from basics to advanced projects and practical applications.”

Yuqori yangilanish chastotasi (oxirgi ma’lumot 09 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Taʼlim toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.

49 093

Obunachilar

+3424 soatlar

+1257 kunlar

+50230 kunlar

1 363

Post ko'rishlar

~ 58224 soatlar

~ 76548 soatlar

2.78%

Muloqot nisbati

~ 2

Kuniga postlar

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⌨️ #Python Celery for Distributed Tasks and Parallel Programming [EN] 🎓 What will you learn?

Learn to analyze data using Pandas and Spark, and create background tasks using Celery and RabbitMQ. This course covers loading data from various sources, processing large amounts of data using DataFrame, running parallel tasks, and integrating with Kafka JDBC Connector.

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