现已上线！2025 年 Telegram 研究 — 年度关键洞察 
Linkedin Learning
前往频道在 Telegram
Linkedin Learning Download and watch Linkedin Learning Courses 📈 Pᴀɪᴅ ᴀᴅs : https://telega.io/c/linkedin_learning
显示更多📈 Telegram 频道 Linkedin Learning 的分析概览
频道 Linkedin Learning (@linkedin_learning) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 216 797 名订阅者，在 教育 类别中位列第 384，并在 印度 地区排名第 717 位。
📊 受众指标与增长动态
自 невідомо 创建以来，项目保持高速增长，吸引了 216 797 名订阅者。
根据 29 六月, 2026 的最新数据，频道保持稳定运转。过去 30 天订阅人数变化为 -278，过去 24 小时变化为 -117，整体触达仍然可观。
- 认证状态： 未认证
- 互动率 (ER)： 平均受众互动率为 7.49%。内容发布后 24 小时内通常能获得 1.81% 的反应，占订阅者总量。
- 帖子覆盖： 每篇帖子平均可获得 16 231 次浏览，首日通常累积 3 932 次浏览。
- 互动与反馈： 受众积极参与，单帖平均反应数为 15。
- 主题关注点： 内容集中在 author, linkedin, linux, javascript, 040k| 等核心主题上。
📝 描述与内容策略
作者将该频道定位为表达主观观点的平台：
“Linkedin Learning
Download and watch Linkedin Learning Courses
📈 Pᴀɪᴅ ᴀᴅs :
https://telega.io/c/linkedin_learning”
凭借高频更新（最新数据采集于 30 六月, 2026），频道始终保持新鲜度与高覆盖。分析显示受众积极互动，使其成为 教育 类别中的关键影响点。
216 797
订阅者
-11724 小时
-3367 天
-27830 天
帖子存档
216 797
🔰 Storytelling for Data and Design
🎟2022-08-17 • ⏱58m • 💡Beginner + Intermediate
🗣 Lachezar Arabadzhiev
Want to become a better storyteller? Tune into this course to learn how to visualize and convey more compelling stories, regardless of your industry, using the tools within Canva.
📦 Topics: Canva, Visual Storytelling
LinkedIn Learning
216 797
📁 Full description
The quality of the predictions coming out of your machine learning model is a direct reflection of the data you feed it during training. Feature engineering helps you extract every last bit of value out of data. This course provides the tools to take a data set, tease out the signal, and throw out the noise in order to optimize your models. The concepts generalize to nearly any kind of machine learning algorithm. Instructor Derek Jedamski provides a refresher on machine learning basics and a thorough introduction to feature engineering. He explores continuous and categorical features and shows how to clean, normalize, and alter them. Learn how to address missing values, remove outliers, transform data, create indicators, and convert features. In the final chapters, Derek explains how to prepare features for modeling and provides four variations for comparison, so you can evaluate the impact of cleaning, transforming, and creating features through the lens of model performance.
216 797
🔰 Applied Machine Learning: Feature Engineering
🎟2020-08-10 • ⏱2h 26m • 💡Intermediate
🗣 Derek Jedamski
Extract the maximum value from your data using feature engineering. Learn how to clean, normalize, and create features to improve the performance of your machine learning models.
📦 Topics: Machine Learning
LinkedIn Learning
216 797
📁 Full description
What would you do if you had an extra 10 hours per week? Sounds impossible? In this course, productivity expert Dave Crenshaw shows you how to get more done in the shortest time possible and give you more of that precious free time. The course lays out the theoretical and practical foundations for being more productive and explains the obstacles that can get in the way. It then gives practical strategies for increasing productivity in three main areas: How to develop habits to be more organized and reduce the clutter in your workspace; how to stay mentally on task and eliminate the to-dos you have floating in your head; and how to develop a time budget to get the most done during your workday and focus on your most valuable activities. If youve been looking for strategies to help you manage your time more efficiently, this course may be well worth your time.
216 797
🔰 Time Management Fundamentals
🎟2022-02-08 • ⏱1h 47m • 💡General
🗣 Dave Crenshaw
Get time management strategies to stay organized, keep a clear mind, and be more productive—in work and life.
📦 Topics: Time Management
LinkedIn Learning
216 797
📁 Full description
Problems are nothing new, but how do we get to the root causes of the problems and fix them? In this course, Sam Yankelevitch addresses root cause analysis and how you can make it work for your business. Sam defines root cause analysis (RCA) and explains how to work with others to find root causes. He describes how to build a Pareto chart to separate vital causes from trivial ones, then goes into the Is/Is Not method, process mapping, fishbone diagrams, five whys analysis, and more. Sam discusses how you can combine different root cause analysis methods and offers tips and suggestions to make your root cause analysis process more effective and efficient. He finishes up with an exploration of the importance of RCA for your business.
216 797
🔰 Root Cause Analysis: Getting to the Root of Business Problems
🎟2022-04-04 • ⏱37m • 💡Beginner
🗣 Sam Yankelevitch
Learn how to solve your businesss problems at their root with sustainable solutions.
📦 Topics: Root Cause Analysis, Business Analysis
LinkedIn Learning
216 797
📁 Full description
Learn how to find and translate complex raw data into information you can use to make better decisions. Access expert Adam Wilbert explains how to create real-world queries to filter and sort data and perform calculations, as well as refine query results with built-in functions, all while offering challenges that help you master the material. Find out how to identify top performers, automate repetitive analysis tasks, make queries more flexible with parameter requests, and increase accuracy and consistency in your database using program flow functions. Adam closes with an assortment of useful query tricks. Take the challenges posed along the way to test and practice your new Access skills.
