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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
Mostrar más📈 Análisis del canal de Telegram AI & Coding Resources 👨💻📑🚀
El canal AI & Coding Resources 👨💻📑🚀 (@codetreasure) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 38 620 suscriptores, ocupando la posición 3 557 en la categoría Tecnologías y Aplicaciones y el puesto 10 676 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 38 620 suscriptores.
Según los últimos datos del 09 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -581, y en las últimas 24 horas de -11, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 15.15%. Durante las primeras 24 horas tras publicar, el contenido suele obtener N/A% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 5 852 visualizaciones. En el primer día suele acumular 0 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 26.
- Intereses temáticos: El contenido se centra en temas clave como humva, hunt, techinnovation, integration, insight.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“👉 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...”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 10 junio, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.
38 620
Suscriptores
-1124 horas
-1187 días
-58130 días
Carga de datos en curso...
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Publicaciones del Canal
https://www.instagram.com/reel/DYzb5VMy0MT/?igsh=aG1lamNvNG1vOTlm
TCS Mass Hiring 2026 !
| 2 | 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? | 10 301 |
| 3 |  Sin texto... | 5 352 |
| 4 | https://www.instagram.com/reel/DYXMuIxS_Jv/?igsh=MXFmMjdlamNjYmV1Zw==
Google is hiring for 2026 Summer Interns | 3 263 |
| 5 | Google Summer Internship 2026 🔥
https://www.instagram.com/reel/DYXMuIxS_Jv/?igsh=MXFmMjdlamNjYmV1Zw== | 0 |
| 6 | Google Summer Internship 2026 🔥
https://www.instagram.com/reel/DYXMuIxS_Jv/?igsh=MXFmMjdlamNjYmV1Zw== | 0 |
| 7 | 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? | 14 899 |
| 8 |  Sin texto... | 2 836 |
| 9 | https://www.instagram.com/reel/DYR6ZLayelw/?igsh=d3hnazhuM3VuNHR0
HIRING REALITY 2026!😮
Do checks this out before your next Job switch. 😋 | 3 198 |
| 10 | 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!💜🙏🏻💜 | 0 |
| 11 | 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? | 0 |
| 12 |  Sin texto... | 0 |
| 13 | Most people trying to learn AI in 2026 are doing it wrong.
Here’s the reality of learning AI today:
↳ Tools change every week
↳ Tutorials are fragmented
↳ Fundamentals are often skipped
The problem isn’t lack of content.
It’s lack of structure
1. Start with tools first
❌ OLD: Learn ChatGPT, agents, tools first
✅ NEW: Tools change fast. Fundamentals don’t
Understanding models, data, and workflows gives long-term leverage
2. Learn from random tutorials
❌ OLD: YouTube + scattered resources are enough
✅ NEW: Random learning creates gaps
Structured paths across AI, ML, and Data Science compound better
3. Focus only on prompting
❌ OLD: Prompting = AI mastery
✅ NEW: Prompting is just the interface
Real value comes from building systems
4. Consume more, build less
❌ OLD: Keep learning before building
✅ NEW: Small projects teach faster than passive content
5. Learn AI in isolation
❌ OLD: Just learn AI
✅ NEW: AI + Data + Product thinking is the real edge
What actually works:
↳ Structured learning paths
↳ Hands-on projects
↳ Layered skill building across domains
With how fast AI is evolving right now, unstructured learning just doesn’t keep up anymore.
Recently, I shifted towards a more structured approach instead of jumping between random resources.
Having access to guided learning paths across AI and Machine Learning makes it easier to stay consistent and actually build skills.
Also noticed a Spring offer right now:
Coursera Plus is available at ₹7,999 for a year (earlier ₹13,999)
Click here to explore the Spring offer: https://imp.i384100.net/c/4788814/3812616/14726
AI isn’t just about using tools anymore.
It’s about understanding and building with them.
Are you currently building AI projects or mostly consuming content? | 0 |
| 14 |  Sin texto... | 0 |
| 15 |  I tested SurfSense, and what stood out immediately is the control it gives you over your data.
Unlike most AI tools that rely on external servers, SurfSense is open source and self-hostable, which means you can run everything on your own infrastructure.
Your data stays with you. Always.
At the same time, it connects your entire workflow into one system.
You can bring in data from tools like Slack, Notion, Gmail, GitHub, and Google Drive, and turn it into a unified, searchable knowledge base.
Then just ask questions in plain English, and it pulls answers across all your sources with context.
It also goes beyond just answers.
You can generate reports, summaries, research briefs, presentations, and even videos directly from your connected data.
Everything is created from your sources, so the output stays accurate and consistent.
It feels less like a tool and more like your own private AI system.
If privacy and control matter to you, this is worth checking out.
Try it here: https://www.surfsense.com/ | 0 |
