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Linkedin Learning

Linkedin Learning

الذهاب إلى القناة على Telegram

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

إظهار المزيد

📈 نظرة تحليلية على قناة تيليجرام Linkedin Learning

تُعد قناة Linkedin Learning (@linkedin_learning) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 216 960 مشتركاً، محتلاً المرتبة 386 في فئة التعليم والمرتبة 721 في منطقة الهند.

📊 مؤشرات الجمهور والحراك

منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 216 960 مشتركاً.

بحسب آخر البيانات بتاريخ 02 يوليو, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار -95، وفي آخر 24 ساعة بمقدار 83، مع بقاء الوصول العام مرتفعاً.

  • حالة التحقق: غير موثّقة
  • معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 6.82‎%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 1.87‎% من ردود الفعل نسبةً إلى إجمالي المشتركين.
  • وصول المنشورات: يحصل كل منشور على متوسط 14 787 مشاهدة. وخلال اليوم الأول يجمع عادةً 4 053 مشاهدة.
  • التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 12.
  • الاهتمامات الموضوعية: يركز المحتوى على مواضيع رئيسية مثل author, linkedin, linux, javascript, 040k|.

📝 الوصف وسياسة المحتوى

يصف المؤلف القناة بأنها مساحة للتعبير عن الآراء الذاتية:
Linkedin Learning Download and watch Linkedin Learning Courses 📈 Pᴀɪᴅ ᴀᴅs : https://telega.io/c/linkedin_learning

بفضل وتيرة التحديث المرتفعة (أحدث البيانات بتاريخ 03 يوليو, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التعليم.

216 960
المشتركون
+8324 ساعات
-2627 أيام
-9530 أيام
أرشيف المشاركات
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Python for Non-Programmers @Linkedin_Learning

📁 Full description Did you know that learning Python is one of the easiest ways to learn to code? It’s true. And in this course you can avoid the jargon and make learning how to code a lot more fun. You don’t have to be an expert technician, either. Join instructor Nick Walter and find out what you need to get started now.In this course, Nick teaches the fundamentals of Python to you: a non-programmer, a user with little to no coding experience. Learn more about what Python is, and what it is and isn’t used for. Explore how Python works with numbers and how you can interact with simple programs such as a simple number-guessing game. Find out how to work with text in Python by building a reusable function to count the words in a block of text. And along the way, tackle quick challenges and other games that allow you to put your new skills to the test.

🔰 Python for Non-Programmers 🎟2021-12-17 • ⏱1h 55m • 💡Beginner 🗣 Nick Walter Explore the basics of Python in a course des
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Improving Your Thinking @Linkedin_Learning

📁 Full description Say you wanted to get better at thinking. Where would you even start? The idea on its own is so abstract. But becoming a better thinker is attainable, and with it come some real-world results, like improvements to your relationships, career, mental health, and emotional intelligence, to name just a few. In this course, philosophy instructor Alyssa Lowery walks you through some of the best ways to improve your thinking.Find out what to do, and what not to do, when tackling a complicated idea, problem, or conversation. Get strategies to improve your intellectual humility and avoid common errors in reasoning. Explore distinctions, arguments, sources, generalizations, thought experiments, and more. It’s easy to think of thinking as an isolated, solitary activity. By the end of this course, you’ll have a better idea about why that’s not the case, how thinking happens with other people, and how you can join them in conversation to take your own thinking to the next level.This course was created by Madecraft. We are pleased to host this training in our library.

🔰 Improving Your Thinking 🎟2022-02-09 • ⏱53m • 💡Beginner 🗣 Alyssa Lowery Get a philosophy instructor’s take on how to thi
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✔️ The most spectacular experiments, slow-motion and the best tricks can now be found in the telegram channel @ExperimentsZ 👀 You won't believe your eyes until you see it! ❗️3 minutes a day with our channel will make your IQ obscenely high❗️ ✅ ExperimentsZ - Be on Top!

Learning Excel What-If Analysis @Linkedin_Learning

📁 Full description Excel is a useful and versatile tool, but did you know you can also use it to analyze hypothetical business cases? Instructor Curt Frye walks you through the complete process. Curt begins by showing you how to create, define, edit, and delete scenarios, then goes into defining data tables. He explains how to use Goal Seek and Solver to create models, define constraints, and require integer solutions. Next, Curt covers ways to organize your analysis worksheet, use checkboxes to turn options on and off, and manipulate a worksheet model to analyze your business. Plus, he defines and demonstrates how to perform a Monte Carlo simulation.

🔰 Learning Excel What-If Analysis 🎟2022-02-08 • ⏱1h 22m • 💡Intermediate 🗣 Curt Frye Find out how to analyze hypothetical
🔰 Learning Excel What-If Analysis 🎟2022-02-08 • ⏱1h 22m • 💡Intermediate 🗣 Curt Frye Find out how to analyze hypothetical business cases in Excel. 📦 Topics: What-if Analysis, Microsoft Excel LinkedIn Learning

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🔰 The Complete Guide to Freelancing in 2022 ⏱ 10 Hours 📦 53 Lessons Start a career or earn a side income by becoming a Free
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📦 Exercice Files

Advanced NLP with Python for Machine Learning @Linkedin_Learning

📁 Full description An incredible amount of unstructured text data is generated every day by social media, web pages, and a variety of other sources. But without the ability to tame and harness that data, you'll be unable to glean any value from it. In this course, learn how to translate messy text data into powerful insights using Python. Instructor Derek Jedamski begins with a quick review of foundational NLP concepts, including how to clean text data and build a model on top of vectorized text. He then jumps into more complex topics such as word2vec, doc2vec, and recurrent neural networks. To wrap up the course, he lends these concepts a real-world context by applying them to a machine learning problem.