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Linkedin Learning

Linkedin Learning

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

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📈 Análisis del canal de Telegram Linkedin Learning

El canal Linkedin Learning (@linkedin_learning) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 217 232 suscriptores, ocupando la posición 389 en la categoría Educación y el puesto 717 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 217 232 suscriptores.

Según los últimos datos del 22 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 166, y en las últimas 24 horas de 15, conservando un alto alcance.

  • Estado de verificación: No verificado
  • Tasa de interacción (ER): El promedio de interacción de la audiencia es 7.10%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.31% de reacciones respecto al total de suscriptores.
  • Alcance de las publicaciones: Cada publicación recibe en promedio 15 413 visualizaciones. En el primer día suele acumular 2 837 visualizaciones.
  • Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 14.
  • Intereses temáticos: El contenido se centra en temas clave como author, linkedin, linux, javascript, 040k|.

📝 Descripción y política de contenido

El autor describe el recurso como un espacio para expresar opiniones subjetivas:
Linkedin Learning Download and watch Linkedin Learning Courses 📈 Pᴀɪᴅ ᴀᴅs : https://telega.io/c/linkedin_learning

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 23 junio, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Educación.

217 232
Suscriptores
+1524 horas
+217 días
+16630 días
Archivo de publicaciones
🚀 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

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📦 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

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🔅 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

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💁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