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Linkedin Learning

Linkedin Learning

Kanalga Telegram’da o‘tish

Linkedin Learning Download and watch Linkedin Learning Courses 📈 Pᴀɪᴅ ᴀᴅs : https://telega.io/c/linkedin_learning

Ko'proq ko'rsatish

📈 Telegram kanali Linkedin Learning analitikasi

Linkedin Learning (@linkedin_learning) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 217 154 obunachidan iborat bo'lib, Taʼlim toifasida 392-o'rinni va Hindiston mintaqasida 733-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 217 154 obunachiga ega bo‘ldi.

16 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 285 ga, so‘nggi 24 soatda esa 9 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 6.48% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 2.05% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 14 071 marta ko‘riladi; birinchi sutkada odatda 4 460 ta ko‘rish yig‘iladi.
  • Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 14 ta reaksiya keladi.
  • Tematik yo‘nalishlar: Kontent author, linkedin, linux, javascript, 040k| kabi asosiy mavzularga jamlangan.

📝 Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
Linkedin Learning Download and watch Linkedin Learning Courses 📈 Pᴀɪᴅ ᴀᴅs : https://telega.io/c/linkedin_learning

Yuqori yangilanish chastotasi (oxirgi ma’lumot 17 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.

217 154
Obunachilar
+924 soatlar
+787 kunlar
+28530 kunlar
Postlar arxiv
📦 Exercise Files

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🔅 Building Tools with Python 📝 Streamline workflows by developing custom tools with Python. Learn about designing for end u
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🔅 Practical Python for Time Series Analysis 📝 Master time series data manipulation, visualization, analysis and regression
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