Linkedin Learning
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Linkedin Learning Download and watch Linkedin Learning Courses 📈 Pᴀɪᴅ ᴀᴅs : https://telega.io/c/linkedin_learning
Mostrar más📈 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 217 335 suscriptores, ocupando la posición 387 en la categoría Educación y el puesto 707 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 217 335 suscriptores.
Según los últimos datos del 10 julio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 243, y en las últimas 24 horas de 106, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 6.78%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.86% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 14 743 visualizaciones. En el primer día suele acumular 4 040 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 16.
- 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 11 julio, 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.
217 335
Suscriptores
+10624 horas
+3557 días
+24330 días
Archivo de publicaciones
217 319
📁 Full description
Data scientists often favor pandas, because it lets them work efficiently with larger amounts of data—a useful quality as data sets become bigger and bigger. In this course, instructor Miki Tebeka shows you how to improve your pandas’ code’s speed and efficiency. First, Miki explains why performance matters and how you can measure it with Python profilers. Then, the course teaches you how to use vectorization to manipulate data. The course also walks through some common mistakes and how to address them.Python and pandas have many high-performance built-in functions, and Miki covers how to use them. Pandas can use a lot of memory, so Miki offers good tips on how to save memory. The course demonstrates how to serialize data with SQL and HDF5. Then Miki goes over how to speed up your code with Numba and Cython. Alternative DataFrames can also speed up your code, and Miki steps through some options. Plus, explore a few extra resources that you can check out.
Udemy Courses - ZTM Courses - Course
217 319
🔰 Faster pandas
🎟2020-11-18 • ⏱1h 24m • 💡Advanced
🗣 Miki Tebeka
Learn how to make your pandas code quicker and more efficient. This course covers vectorization, common mistakes, pandas performance, saving memory, Numba, Cython, and more.
📦 Topics: Data Manipulation, Pandas, Data Analysis
LinkedIn Learning
217 319
📁 Full description
When the concept of marketing integration comes up, many people automatically think about external customer marketing; however, external approaches—advertising, social media, and event marketing, for example—are just one piece of the puzzle. In this course, Dina Shapiro shares a comprehensive brand and marketing integration approach that encompasses all external and internal stakeholders and touchpoints. Along with going over external marketing, Dina covers three other important types of integration: vertical, horizontal, and internal. She also explores common roadblocks and shows how to incorporate integration strategies into your own company.
Udemy Courses - ZTM Courses - Course
217 319
🔰 Brand and Marketing Integration
🎟2017-03-01 • ⏱59m • 💡Intermediate
🗣 Dina Shapiro
Learn how to leverage the four types of brand and marketing integration—vertical, horizontal, external, and internal—to successfully reach all of your stakeholders.
📦 Topics: Brand Marketing, Brand Management
LinkedIn Learning
217 319
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217 319
🔰 The Complete Junior to Senior Web Developer Roadmap (2021)
⏱ 36.5 Hours 📦 420 Lessons
Ultimate coding interview bootcamp. Get more job offers, negotiate a raise, and learn everything you need to get the job you want!
Taught by: Andrei Neagoie
Download Full Course: https://t.me/joinchat/EWli8dC-A5RmMGE0
217 319
📁 Full description
While we often think of creativity as an inherent trait, anyone—whether they're an artist or an actuary—can learn how to be more creative. In this course, explore the different ways to learn creativity, and discover how to be more creative both on an individual basis and in a team setting. Instructor Drew Boyd shares the importance and power of creativity, goes over the barriers to creativity, and shows you some behaviors and techniques that can help you generate novel ideas or solutions to problems, as an individual. He covers ways to create a creativity dream team, facilitate effective group sessions for a better creative output, select the best ideas, and more.
Udemy Courses - ZTM Courses - Course
217 319
🔰 Thinking Creatively
🎟2017-04-12 • ⏱41m • 💡Beginner
🗣 Drew Boyd
Learn behaviors and techniques that can help you be more creative as an individual and as part of a team.
📦 Topics: Creativity Skills
LinkedIn Learning
217 319
📁 Full description
Do you need to learn Python for your current job, for the job you want, or just for fun? In this course, instructor Ronnie Sheer shows you how you can leverage your existing knowledge of JavaScript to get started programming in Python. Ronnie compares Python and JavaScript, then covers how to set up and run a Python environment. He discusses how to write code that adheres to Python conventions, which can prevent bugs. Ronnie explains some of the basic logic in Python, including the use of indentation, how to write and debug control flow, how to use Python try/except appropriately, and more. He goes over objects and class definitions, then explores Python’s data model feature and mixins class. Ronnie goes into iteration in Python and shows how you can write more concise and elegant code in Python by using zip, enumerate, and list comprehensions. He concludes with a challenge that shows you how to apply your knowledge of JavaScript and Python to improve a small program.
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