uz
Feedback
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 217 232 obunachidan iborat bo'lib, Taʼlim toifasida 389-o'rinni va Hindiston mintaqasida 717-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 217 232 obunachiga ega bo‘ldi.

22 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 166 ga, so‘nggi 24 soatda esa 15 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 7.10% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.31% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 15 413 marta ko‘riladi; birinchi sutkada odatda 2 837 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 23 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.

217 232
Obunachilar
+1524 soatlar
+217 kunlar
+16630 kunlar
Postlar arxiv
🚀 Even students earn $100 per day! 10 years ago the Bitcoin costed only 10 cents, and today it’s $55k. Everyone who invested
🚀 Even students earn $100 per day! 10 years ago the Bitcoin costed only 10 cents, and today it’s $55k. Everyone who invested then $10 already became a millionaire. 💰 Since the beginning of autumn the cryptocurrency has grown up in 3-4 times and it’s just a beginning. Don’t miss the opportunities! Right now the founder of the biggest channel on this theme Coin Post opens access to a private channel, where he shows the ways to earn thousands dollars on cryptocurrency. Subscribe or you’ll miss your chance to become rich. 👇 #ad

import socket import struct import time import pyModeS as pms import sqlite3 # Import the sqlite3 library # Define multicast group, port, and network device (interface) multicast_group = '224.0.0.1' port = 5555 network_device = 'your_network_device_name_or_ip' # Replace with your network device # Create a UDP socket and specify the network device sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) sock.setsockopt(socket.SOL_SOCKET, socket.SO_BINDTODEVICE, network_device.encode()) # Bind to the server address (multicast group) sock.bind(('', port)) # Join the multicast group group = socket.inet_aton(multicast_group) mreq = struct.pack('4sL', group, socket.INADDR_ANY) sock.setsockopt(socket.IPPROTO_IP, socket.IP_ADD_MEMBERSHIP, mreq) # Define the capture interval in seconds capture_interval = 5 # Adjust this value as needed (e.g., 5 seconds) # Connect to the SQLite database (or create it if it doesn't exist) conn = sqlite3.connect('asterix_data.db') # Replace 'asterix_data.db' with your desired database filename cursor = conn.cursor() # Create a table to store the data (if it doesn't exist) cursor.execute('''CREATE TABLE IF NOT EXISTS captured_data ( id INTEGER PRIMARY KEY AUTOINCREMENT, icao24 TEXT, altitude INTEGER, velocity INTEGER, callsign TEXT )''') # Function to insert data into the SQLite database def insert_data(icao24, altitude, velocity, callsign): cursor.execute("INSERT INTO captured_data (icao24, altitude, velocity, callsign) VALUES (?, ?, ?, ?)", (icao24, altitude, velocity, callsign)) conn.commit() # Commit the transaction def process_and_save_data(asterix_data): try: msg = pms.hex2bin(asterix_data) icao24 = pms.icao(msg) altitude = pms.altitude(msg) velocity = pms.velocity(msg) callsign = pms.callsign(msg) # Display the extracted data print("ICAO24:", icao24) print("Altitude:", altitude) print("Velocity:", velocity) print("Callsign:", callsign) # Insert the data into the SQLite database insert_data(icao24, altitude, velocity, callsign) except pms.exceptions.InvalidModeSMessage as e: print("Invalid Asterix message:", e) while True: data, addr = sock.recvfrom(1024) # Adjust buffer size as needed if addr[0] == multicast_group: process_and_save_data(data.decode('utf-8')) # Sleep for the specified capture interval time.sleep(capture_interval)

Stand Out as a Power Performer at Work @Linkedin_Learning

🔸 Full description 🔸 Setting the bar high and being great at your job often dovetail with your performance. But how do you break the mold, assert yourself more authentically, and stand out like a rockstar when it comes to work? In this course, instructor Nicole Dove guides you through the process of identifying what it means to be great at your job, moving from good to great, aligning your work with your true sense of purpose, showcasing your strengths, and creating strategies to get better results.Learn how to develop your reputation in a way that gets you noticed for what you do, from working toward your managers goals to building strong relationships and making bold decisions. Along the way, Nicole shares advice drawn from experience on how to start tracking your progress with metrics that matter and sharing your wins to drive future growth.

🔅 Stand Out as a Power Performer at Work 🌐 Author: Nicole Dove 🔰 Level: General ⏰ Duration: 31m 🌀 Start your journey as a
🔅 Stand Out as a Power Performer at Work 🌐 Author: Nicole Dove 🔰 Level: GeneralDuration: 31m 🌀 Start your journey as a power performer who delivers authentically and stands out at work. 📗 Topics: Performance Improvement 📤 Join @linkedin_learning for more courses

hr.webp0.09 KB

📦 Exercice Files

Learning Teradata Vantage @Linkedin_Learning

🔸 Full description 🔸 Explore Teradata, a powerful analytics tool, with an example Python application. Instructor Kishan Iyer walks you through the basics of Teradata Vantage, plus tables, connections, performing operations, and querying data. Kishan explains several advantages of using Teradata Vantage. He shows you the architecture of Teradata Vantage, as well as setting up and launching the Teradata Vantage Express VM, creating a Teradata database, and creating and adding rows to a Teradata table. Kishan goes over the full process of connecting to Teradata from the BTEQ command-line utility. He demonstrates adding columns to existing tables, modifying and removing data and tables, defining tables with the Data Transfer Utility, and creating multiple related tables. Kishan also covers querying data in Teradata, including applying query filters, updating and deleting queries, performing operations from Python, and more. Note: This course was created by Kishan Iyer. We are pleased to host this training in our library.

🔅 Learning Teradata Vantage 🌐 Author: Kishan Iyer 🔰 Level: Advanced ⏰ Duration: 2h 3m 🌀 Learn how to use Teradata, a powe
🔅 Learning Teradata Vantage 🌐 Author: Kishan Iyer 🔰 Level: AdvancedDuration: 2h 3m 🌀 Learn how to use Teradata, a powerful analytics tool, using an example Python application. 📗 Topics: Teradata 📤 Join @linkedin_learning for more courses

hr.webp0.09 KB

🔅 Data Visualizations with Plotly 🌐 Author: Brett Vanderblock 🔰 Level: Beginner ⏰ Duration: 55m 🌀 Learn how to create int
🔅 Data Visualizations with Plotly 🌐 Author: Brett Vanderblock 🔰 Level: BeginnerDuration: 55m 🌀 Learn how to create interactive data visualizations that can be shared online or offline using Plotly. 📗 Topics: Data Visualization, Plotly 📤 Join @python_trainings for more courses

hr.webp0.09 KB

💁6 months before the Bitcoin halving – are you ready for the bull market? Look at the screenshot from 2019. Anyone could hav
💁6 months before the Bitcoin halving – are you ready for the bull market? Look at the screenshot from 2019. Anyone could have bought BNB or MATIC and turned $100 into $10,000. No one knew what is BNB or MATIC back then.Now is 2023. Do you know what LayerZero or Venom is?Follow AltLex to not miss the bull run profits – https://t.me/+pLcmrd_o4VFiOWM1

👇📈 Pᴀɪᴅ ᴀᴅ WITH : https://telega.io/c/linkedin_learning

🚀 Even students earn $100 per day! 10 years ago the Bitcoin costed only 10 cents, and today it’s $55k. Everyone who invested
🚀 Even students earn $100 per day! 10 years ago the Bitcoin costed only 10 cents, and today it’s $55k. Everyone who invested then $10 already became a millionaire. 💰 Since the beginning of autumn the cryptocurrency has grown up in 3-4 times and it’s just a beginning. Don’t miss the opportunities! Right now the founder of the biggest channel on this theme Coin Post opens access to a private channel, where he shows the ways to earn thousands dollars on cryptocurrency. Subscribe or you’ll miss your chance to become rich. 👇 #ad

📦 Exercice Files

Excel: Financial Functions in Depth @Linkedin_Learning

🔸 Full description 🔸 Analyzing financial data can seem intimidating, but Microsoft Excel has a wide range of functions to perform these calculations quickly and easily. In this course, Microsoft MVP Danielle Stein Fairhurst shows you how and when to use each of the financial functions available in Excel. Danielle covers evaluating loans, payments, and interest; calculating depreciation; determining rates of return; calculating prices and yields as well as applying some of the new features of Excel for Microsoft 365 to financial data. Plus, she guides you through combining these functions to perform financial analysis.

🔅 Excel: Financial Functions in Depth 🌐 Author: Danielle Stein Fairhurst 🔰 Level: Intermediate ⏰ Duration: 2h 23m 🌀 Learn
🔅 Excel: Financial Functions in Depth 🌐 Author: Danielle Stein Fairhurst 🔰 Level: IntermediateDuration: 2h 23m 🌀 Learn to use Excel functions for financial analysis. Find out how to calculate loan payments, depreciation, rate of return, and more, in Microsoft Excel. 📗 Topics: Financial Analysis, Microsoft Excel 📤 Join @linkedin_learning for more courses