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AI & Coding Resources 👨‍💻📑🚀

AI & Coding Resources 👨‍💻📑🚀

前往频道在 Telegram

👉 Sharing Free Technical and Coding realted Resources and handwritten Notes 🤩📑👨‍💻. 👉 Follow on LinkedIn for more content :- https://www.linkedin.com/in/manish-kumar-shah 👉 Follow on Instagram for Short Notes :- https://instagram.com/codes.manish

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📈 Telegram 频道 AI & Coding Resources 👨‍💻📑🚀 的分析概览

频道 AI & Coding Resources 👨‍💻📑🚀 (@codetreasure) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 38 146 名订阅者,在 技术与应用 类别中位列第 3 522,并在 印度 地区排名第 10 342

📊 受众指标与增长动态

невідомо 创建以来,项目保持高速增长,吸引了 38 146 名订阅者。

根据 11 七月, 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 -444,过去 24 小时变化为 -19,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 5.83%。内容发布后 24 小时内通常能获得 N/A% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 2 223 次浏览,首日通常累积 0 次浏览。
  • 互动与反馈: 受众积极参与,单帖平均反应数为 4
  • 主题关注点: 内容集中在 humva, hunt, techinnovation, integration, insight 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:
👉 Sharing Free Technical and Coding realted Resources and handwritten Notes 🤩📑👨‍💻. 👉 Follow on LinkedIn for more content :- https://www.linkedin.com/in/manish-kumar-shah 👉 Follow on Instagram for Short Notes :- https://instagram.com/codes.m...

凭借高频更新(最新数据采集于 12 七月, 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 技术与应用 类别中的关键影响点。

38 146
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频道帖子
One of the biggest mistakes companies are making with AI right now? Building critical workflows around a single AI model. The AI landscape is moving too fast. Models improve, pricing changes, and new capabilities emerge constantly. If your business is locked into one provider, you're limiting your ability to adapt. That's why Rebel by Mindstone caught my attention. What started with Joshua Wohle's personal operating system has evolved into a platform designed to help organizations adopt AI at scale—without locking themselves into a single model or vendor. Instead of isolated AI tools and disconnected experiments, Rebel gives every employee their own AI agent while keeping workflows portable across different AI providers. And this isn't just a concept. Epignosis, the company behind TalentLMS (22M+ users), recently rolled Rebel out to all 250 employees across engineering, sales, finance, product, and customer success. Twelve weeks later, they reported gaining the equivalent capacity of 8 full-time employees. A few things that stood out to me: • Works across multiple AI providers, so you're never locked into one model. • Connects with email, CRM, Slack, calendars, and documents. • Can run locally, keeping sensitive data under your control. • Includes approval layers before taking actions on your behalf. • Builds shared organizational memory so knowledge compounds over time. The memory piece is especially interesting. As people create workflows, automate tasks, and solve problems, that knowledge becomes available across the organization instead of being trapped in individual chats. Mindstone has now fair-sourced Rebel, making it free for individuals and organizations with up to 100 users. If you're thinking about how to roll out AI across an entire company—not just for a handful of power users—Rebel is worth checking out. 🔗 Download Rebel: https://rebel.mindstone.com/ 🔗 Product Hunt: https://www.producthunt.com/products/mindstone-rebel #Mindstone #AI

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https://www.instagram.com/reel/DYzb5VMy0MT/?igsh=aG1lamNvNG1vOTlm TCS Mass Hiring 2026 !
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Cybersecurity is no longer just a tech skill. It’s becoming a basic digital survival skill. Almost everything today lives online: • Banking • Remote work • Social media • Cloud storage • AI tools • Online payments & personal data Which also means cyber threats are evolving faster than ever. What surprised me recently is how many attacks still happen because of simple mistakes: • Weak passwords • Fake emails • Unsafe downloads • Poor security awareness And with AI making scams more convincing, understanding cybersecurity fundamentals is becoming valuable across almost every profession, not just IT roles. That’s one reason I’ve been exploring structured cybersecurity learning lately instead of randomly consuming content online. Platforms like Coursera have beginner friendly cybersecurity programs that help break down concepts in a practical way. Some interesting courses I came across: Cyber Security Fundamentals: https://imp.i384100.net/B5ynbx Cybersecurity Essentials: https://imp.i384100.net/GbVKVr Data Privacy: https://imp.i384100.net/1GP9Ra Ethical Hacking: https://imp.i384100.net/4amGyM Network Security: https://imp.i384100.net/yZbqjv Google Cybersecurity Certificate: https://imp.i384100.net/Or5L6G They make the learning process much easier to follow step by step. What’s one cybersecurity habit you think everyone should follow daily?
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https://www.instagram.com/reel/DYXMuIxS_Jv/?igsh=MXFmMjdlamNjYmV1Zw== Google is hiring for 2026 Summer Interns
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Google Summer Internship 2026 🔥 https://www.instagram.com/reel/DYXMuIxS_Jv/?igsh=MXFmMjdlamNjYmV1Zw==
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Google Summer Internship 2026 🔥 https://www.instagram.com/reel/DYXMuIxS_Jv/?igsh=MXFmMjdlamNjYmV1Zw==
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Machine Learning looks exciting when you see the final results. AI tools. Smart automations. Models doing things that felt impossible a few years ago. But when I actually started learning ML seriously, I realized how easy it is to feel completely lost. One tutorial explains algorithms. Another jumps into Python libraries. Then suddenly you’re watching a long neural network video without properly understanding the basics behind it. That’s where a lot of people get stuck. I’ve been spending more time learning Machine Learning recently, and one thing that genuinely helped me was following a more structured learning path instead of constantly switching between random resources. While exploring coursera courses, I liked how the courses are organized from foundational concepts to more advanced ML topics. You can gradually move through: • Python for ML: https://imp.i384100.net/eKJOOZ • Data preprocessing: https://imp.i384100.net/Jk26Mq • Regression + classification: https://imp.i384100.net/g1KJEA • Supervised and unsupervised learning: https://imp.i384100.net/0GP6vR • Neural networks: https://imp.i384100.net/DKrLn2 • Deep Learning projects: https://imp.i384100.net/jroLxe What personally helped me most was learning concepts in sequence instead of trying to figure everything out alone from scattered tutorials. And honestly, with AI evolving this fast, understanding the fundamentals feels more important than ever. I’ve also noticed that many people rush into using AI tools before understanding how Machine Learning actually works underneath. For anyone learning ML right now: What concept took you the longest to finally understand?
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https://www.instagram.com/reel/DYR6ZLayelw/?igsh=d3hnazhuM3VuNHR0 HIRING REALITY 2026!😮 Do checks this out before your next Job switch. 😋
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https://www.instagram.com/p/DYKY1vEkm39/?igsh=MWZncmNnN3AwbXJhcQ== Hello Everyone! Just getting started on my new journey as an Instagram content creator. Sharing what I learn, build & experience around tech, AI, career & life 💻🤖☕ First reel dropping soon👀💖 Do LIKE FOLLOW SHARE my page! Need your immense support!💜🙏🏻💜
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