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Artificial Intelligence

Artificial Intelligence

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πŸ“ˆ Analytical overview of Telegram channel Artificial Intelligence

Channel Artificial Intelligence (@artificial_intelligence_com) in the English language segment is an active participant. Currently, the community unites 70 501 subscribers, ranking 1 845 in the Technologies & Applications category and 4 749 in the India region.

πŸ“Š Audience metrics and dynamics

Since its creation on Π½Π΅Π²Ρ–Π΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 70 501 subscribers.

According to the latest data from 17 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 1 211 over the last 30 days and by -3 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 7.55%. Within the first 24 hours after publication, content typically collects 2.04% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 5 325 views. Within the first day, a publication typically gains 1 437 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 10.
  • Thematic interests: Content is focused on key topics such as learning, linkedin, linux, udemy, 040k|.

πŸ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
β€œπŸ”’ Welcome Artificial Intelligence Channel Buy ads: https://telega.io/c/Artificial_Intelligence_COM”

Thanks to the high frequency of updates (latest data received on 18 June, 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 Technologies & Applications category.

70 501
Subscribers
-324 hours
+2057 days
+1 21130 days
Posts Archive
10. Networking

09. XSS

10. Networking

09. XSS

08. Introduction to XXE

05 - Scientific Literature Review - LLMs

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04 - Basics of Generation Models for RAG - Part 01

03 - Scientific Literature Review - Prompt Engineering

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02 - Basics of Retrieval Systems for RAG and Generative AI - Part 02

01 - RAG and Generative AI with Python

πŸ”— RAG, AI Agents and Generative AI with Python and OpenAI 2025 🌟 4.6 - 553 votes πŸ’° Original Price: $54.99 πŸ“– Mastering Ret
πŸ”— RAG, AI Agents and Generative AI with Python and OpenAI 2025 🌟 4.6 - 553 votes πŸ’° Original Price: $54.99
πŸ“– Mastering Retrieval-Augmented Generation (RAG), Generative AI (Gen AI), AI Agents, Agentic RAG, OpenAI API with Python
πŸ”Š Taught By: Diogo Alves de Resende πŸ“€ Download All Courses

βš οΈπŸ‘† This post will be deleted after 24 hours πŸ‘†βš οΈ

@machine_learning_courses_Machine_Learning_with_Python_Cookbook.pdf8.33 MB

πŸ“™ Machine Learning with Python Cookbook - 2nd Edition πŸ’΅ The book price: 45$
πŸ“™ Machine Learning with Python Cookbook - 2nd Edition πŸ’΅ The book price: 45$

πŸ€– 9 AI TOOLS YOU CAN’T IGNORE IN 2025: βœ… Every creator should be using these: 1. Submagic.co – Captions + emojis 2. Munch.com – Video repurposing 3. Supernormal.com – Meeting notes 4. Cleanup.pictures – Remove objects 5. Vizard.ai – Short-form editor 6. BrieflyAI.com – Idea summarizer 7. Scribehow.com – Auto tutorials 8. Recraft.ai – Vector design 9. Kaiber.ai – AI animations πŸ“Œ Save this if you create content

πŸ€– 85 Useful AI TOOLS... ➑️ Share
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πŸ€– 85 Useful AI TOOLS... ➑️ Share

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πŸ”— Most ML roadmaps If you’re tired of bloated diagrams and endless theory, this one’s for you. This is the 10-step roadmap I
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πŸ”— Most ML roadmaps
If you’re tired of bloated diagrams and endless theory, this one’s for you.
This is the 10-step roadmap I wish someone gave me earlier focused on real-world impact, not just flashy model builds. Swipe through to see: βœ… The core skills you actually need βœ… What separates you from junior talent βœ… What most self-taught engineers skip Whether you’re transitioning from data analyst, coming from software dev, or just trying to stop tutorial-hopping...

πŸ€– 10 UNKNOWN AI TOOLS....
πŸ€– 10 UNKNOWN AI TOOLS....

πŸ“Œ Awesome CursorRules: A repository of Cursor AI recipes. Awesome CursorRules is a collection of .cursorrules recipe files f
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πŸ“Œ Awesome CursorRules: A repository of Cursor AI recipes. Awesome CursorRules is a collection of .cursorrules recipe files for fine-tuning the behavior of Cursor AI. The author of the repository has collected dozens of templates that adapt code generation to specific projects: from mobile applications to blockchain solutions. The main feature of .cursorrules is flexibility. Developers can write rules that will make AI hints more relevant: for example, take into account the team's code style or the architectural features of the project. This not only speeds up the work, but also reduces the risk of errors. The collection includes almost all areas of development: frontend (Angular, NextJS, Qwik, React, Solid, Svelte, Vue), backend (Deno, Elixir, ES, Go, Java, Lavarel, NodeJS, Python, TypeScript, WordPress), mobile development (React Native, SwiftUI, TypeScript, Android, Flutter) and specific tasks - integration with Kubernetes or optimization for SOLID principles. For beginners, there are step-by-step instructions: just copy the file into the project or install the extension for VS Code. Judging by the reviews, Awesome CursorRules has already become a must-have for those who want to get the most out of Cursor AI. πŸ–₯ GitHub