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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
Больше📈 Аналитический обзор Telegram-канала Linkedin Learning
Канал Linkedin Learning (@linkedin_learning) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 216 773 подписчиков, занимая 387 место в категории Образование и 718 место в регионе Индия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 216 773 подписчиков.
Согласно последним данным от 30 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило -326, а за последние 24 часа — -64, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 6.72%. В первые 24 часа после публикации контент обычно набирает 1.81% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 14 556 просмотров. В течение первых суток публикация набирает 3 932 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 12.
- Тематические интересы: Контент сосредоточен на ключевых темах, таких как author, linkedin, linux, javascript, 040k|.
📝 Описание и контентная политика
Автор описывает ресурс как площадку для выражения субъективного мнения:
“Linkedin Learning
Download and watch Linkedin Learning Courses
📈 Pᴀɪᴅ ᴀᴅs :
https://telega.io/c/linkedin_learning”
Благодаря высокой частоте обновлений (последние данные получены 01 июля, 2026) канал поддерживает актуальность и высокий уровень охвата публикаций. Аналитика показывает, что аудитория активно взаимодействует с контентом, что делает его важной точкой влияния в категории Образование.
216 773
Подписчики
-6424 часа
-4767 дней
-32630 день
Архив постов
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
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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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