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Linkedin Learning
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Linkedin Learning Download and watch Linkedin Learning Courses 📈 Pᴀɪᴅ ᴀᴅs : https://telega.io/c/linkedin_learning
Show more📈 Analytical overview of Telegram channel Linkedin Learning
Channel Linkedin Learning (@linkedin_learning) in the English language segment is an active participant. Currently, the community unites 216 773 subscribers, ranking 387 in the Education category and 718 in the India region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 216 773 subscribers.
According to the latest data from 30 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -326 over the last 30 days and by -64 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 6.72%. Within the first 24 hours after publication, content typically collects 1.81% reactions from the total number of subscribers.
- Post reach: On average, each post receives 14 556 views. Within the first day, a publication typically gains 3 932 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 12.
- Thematic interests: Content is focused on key topics such as author, linkedin, linux, javascript, 040k|.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“Linkedin Learning
Download and watch Linkedin Learning Courses
📈 Pᴀɪᴅ ᴀᴅs :
https://telega.io/c/linkedin_learning”
Thanks to the high frequency of updates (latest data received on 01 July, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Education category.
216 773
Subscribers
-6424 hours
-4767 days
-32630 days
Posts Archive
216 783
ANNOUNCEMENT ✍🏻✍🏻✍🏻
This channel is available for advertisements.
More than 64000 international members and daily active users, never sent any spams, this helps in building trust and authority among the members.
You can display your message here. Ads and promotions. No spamming allowed, admin will randomly keep checking your promotion for any unethical use.
To promote with us feel free to contact: @thenano245
Note: If users report negatively about the ads, your ads may get removed.
216 783
📁 Full description
Life is full of hard decisions. From your job to your personal life, every strategic decision you make has a lasting impact. The trouble is, these decisions are based on judgments, and there are all kinds of powerful and invisible forces that cause errors in human judgment, interfering with optimal decision making. In this course, instructor Becki Saltzman helps you gain a better understanding of how to uncover and reduce these error-causing forces to make wiser strategic decisions.Learn about strategic decision errors and what you can do to avoid them. Explore the concepts of noise and bias, the difference between the two, and how to identify and reduce each when youre making strategic decisions, both individually and with your teams. You, too, can avoid the pitfalls of a bad decision—but you need to have a well-designed process that mitigates noise and bias from the get-go.
216 783
🔰 Removing Noise and Bias from Strategic Decision-Making
🎟2022-02-15 • ⏱1h 4m • 💡Advanced
🗣 Becki Saltzman
Explore how to make better strategic decisions by effectively reducing noise and bias in the decision-making process.
📦 Topics: Business Decision Making
LinkedIn Learning
216 783
📁 Full description
Deep Learning as a technology has grown leaps and bounds in the last few years. More and more AI solutions use Deep Learning as their foundational technology. Studying this technology, however, presents several challenges. IT professionals from varying backgrounds need a simplified resource to learn the concepts and build models quickly. In this course, instructor Kumaran Ponnambalam provides a simplified path to understand various optimization and tuning options available for deep learning models and shows you how to use these options to improve models. He begins by reviewing Deep Learning, including artificial neural networks and architectures. Next, Kumaran discusses the process of hyper parameter tuning. He examines the building blocks of neural networks and the levers available to tune them. Kumaran offers recommendations and best practices. Then he concludes with an end-to-end tuning example.
216 783
🔰 Deep Learning: Model Optimization and Tuning
🎟2022-02-01 • ⏱54m • 💡Advanced
🗣 Kumaran Ponnambalam
Learn about various optimization and tuning options available for deep learning models and use them to improve models.
📦 Topics: Deep Learning, Machine Learning
LinkedIn Learning
216 783
📁 Full description
Do you need to learn the essentials of C#? This two-part series shows you through all the basics. In this course, part one of the series, instructor Matt Milner shows you classes, structs, variables, and much more. Matt begins by placing C# in context with .NET, MSIL, and the Base Class Library. He walks you through understanding and working with classes, structs, and records. Then Matt shows you several useful techniques to organize your C# code. He discusses variables in-depth, then dives into how to define, enable, and test enums, as well as how to use nullable types and work with null objects. Matt goes over if, else, and switch statements and covers switch expressions, the is expression, and an introduction to patterns. Plus, he explains several types of patterns and describes how to use guard conditions to further refine your switch case matches.
216 783
🔰 C# Essential Training 1: Types and Control Flow
🎟2022-01-28 • ⏱2h 38m • 💡Beginner
🗣 Matt Milner
Learn about classes, structs, record, organizing C# code, variables, enums, nullable types, and more.
📦 Topics: Control Flow, C#
LinkedIn Learning
216 783
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216 783
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