AI & Coding Resources 👨💻📑🚀
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👉 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
Показати більше📈 Аналітичний огляд Telegram-каналу AI & Coding Resources 👨💻📑🚀
Канал AI & Coding Resources 👨💻📑🚀 (@codetreasure) у мовному сегменті Англійська є активним учасником. На даний момент спільнота об'єднує 37 344 підписників, посідаючи 3 462 місце в категорії Технології та додатки та 10 562 місце у регіоні Індія.
📊 Показники аудиторії та динаміка
З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 37 344 підписників.
За останніми даними від 26 серпня, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на -534, а за останні 24 години на -17, загальне охоплення залишається високим.
- Статус верифікації: Не верифікований
- Рівень залученості (ER): Середній показник залученості аудиторії становить 15.80%. Протягом перших 24 годин після публікації контент зазвичай збирає 16.88% реакцій від загальної кількості підписників.
- Охоплення публікацій: В середньому кожен допис отримує 5 900 переглядів. Протягом першої доби публікація в середньому набирає 6 303 переглядів.
- Реакції та взаємодія: Аудиторія активно підтримує контент: середня кількість реакцій на один пост – 11.
- Тематичні інтереси: Контент зосереджений навколо ключових тем, таких як humva, hunt, techinnovation, integration, insight.
📝 Опис та контентна політика
Автор описує ресурс як майданчик для висловлення суб'єктивної думки:
“👉 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...”
Завдяки високій частоті оновлень (останні дані отримано 27 серпня, 2026), канал підтримує актуальність та високий рівень охоплення публікацій. Аналітика показує, що аудиторія активно взаємодіє з контентом, що робить його важливою точкою впливу в категорії Технології та додатки.
37 344
Підписники
-1724 години
-1197 днів
-53430 день
Архів дописів
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I use AI almost every day for my work.
But recently, I realized something: using AI every day doesn’t necessarily mean you’re using it well.
I wanted to get better at researching, brainstorming, organizing information, improving my writing, and using AI more effectively for my daily tasks.
That’s what caught my attention about the Google AI Professional Certificate on Coursera.
It focuses on practical AI skills, including how to:
→ Work with AI tools like Gemini, NotebookLM, and AI Studio
→ Research, brainstorm, and organize information
→ Improve writing, communication, and productivity
→ Build AI-powered solutions
→ Apply AI to real workplace tasks
→ Complete hands-on projects and a capstone
And for a limited time, enrolling in the certificate also includes 3 months of Google AI Pro at no extra cost.
If you’re looking to build practical AI skills that you can actually use in your work, this is worth checking out.
🔗 Enroll here: https://imp.i384100.net/c/4788814/3979813/14726?sharedid=gwgmanishai
Over the past year, I've realized that AI has become an important skill, no matter what field you work in.
Since I create AI content every day, I'm always looking for better ways to use AI in my work, not just write better prompts.
That's why I decided to explore the Google AI Professional Certificate.
Check out here: https://imp.i384100.net/c/4788814/3979813/14726?sharedid=gwgmanishai
What I like about the program is that it's focused on practical learning. You get to use tools like Gemini, NotebookLM, and AI Studio to:
• Organize research and study materials
• Brainstorm ideas
• Save time on everyday tasks
• Build AI powered projects
The program also includes hands on exercises and a capstone project, so you can apply what you learn, build a portfolio, and earn an industry recognized Professional Certificate from Google.
For a limited time, when you enroll in the Google AI Professional Certificate, you'll also get 3 months of Google AI Pro at no extra cost.
Enroll now: https://imp.i384100.net/c/4788814/3979813/14726?sharedid=gwgmanishai
It can help you:
• Understand complex topics more easily
• Organize your study materials
• Generate ideas for projects
• Build projects more efficiently
• Prepare your resume and practice interview questions
Whether you're a student, creator, developer, or working professional, it's a practical way to build job ready AI skills that you can use in your everyday work.
If you've been thinking about learning AI in a more practical way, this is worth checking out.
🔗 Enroll here: https://imp.i384100.net/c/4788814/3979813/14726?sharedid=gwgmanishai
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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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TCS Mass Hiring 2026 !
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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Google is hiring for 2026 Summer Interns
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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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HIRING REALITY 2026!😮
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Most people think they are learning AI.
But they are actually just collecting tools.
One week it is ChatGPT.
Next week it is a new automation tool.
Then a design or video AI platform.
It feels like progress.
But in reality, it is just noise.
Because without a clear roadmap, every new tool resets you back to zero.
The real shift happens when you stop chasing tools and start building skills step by step.
A simple roadmap most people ignore:
↳ Start with basics like Python and data handling.
↳ Understand statistics and how data actually works.
↳ Learn core Machine Learning concepts.
↳ Build small real-world projects.
↳ Then explore AI tools to apply what you know.
That is what creates real confidence.
Right now, the people growing fastest are not the ones using the most tools.
They are the ones who have strong fundamentals and a clear path.
That is where structured learning makes a difference.
Instead of jumping between random tutorials, you follow a guided path across AI, Data Science, Machine Learning, or even UI UX and Project Management.
I recently came across a Spring offer that gives access to multiple courses under one subscription.
The annual plan is currently ₹7,999 instead of ₹13,999.
Explore the Spring offer here: https://imp.i384100.net/c/4788814/3812616/14726
If you are serious about upskilling this year, having everything in one place makes it easier to stay consistent and actually complete what you start.
Because in the long run, tools will change.
But your foundation and problem-solving ability will not.
Are you building real AI skills right now, or just experimenting with tools?
