Available now! Telegram Research 2025 โ the year's key insights 
AI & Coding Resources ๐จโ๐ป๐๐
Open in Telegram
๐ Sharing Free Technical and Coding realted Resources and handwritten Notes ๐คฉ๐๐จโ๐ป. ๐ Follow on LinkedIn for more content :- https://www.linkedin.com/in/manish-kumar-shah ๐ Follow on Instagram for Short Notes :- https://instagram.com/codes.manish
Show more๐ Analytical overview of Telegram channel AI & Coding Resources ๐จโ๐ป๐๐
Channel AI & Coding Resources ๐จโ๐ป๐๐ (@codetreasure) in the English language segment is an active participant. Currently, the community unites 38 617 subscribers, ranking 3 558 in the Technologies & Applications category and 10 672 in the India region.
๐ Audience metrics and dynamics
Since its creation on ะฝะตะฒัะดะพะผะพ, the project has demonstrated rapid growth, gathering an audience of 38 617 subscribers.
According to the latest data from 10 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -583 over the last 30 days and by -16 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 15.31%. Within the first 24 hours after publication, content typically collects N/A% reactions from the total number of subscribers.
- Post reach: On average, each post receives 5 911 views. Within the first day, a publication typically gains 0 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 26.
- Thematic interests: Content is focused on key topics such as humva, hunt, techinnovation, integration, insight.
๐ Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
โ๐ Sharing Free Technical and Coding realted Resources and handwritten Notes ๐คฉ๐๐จโ๐ป.
๐ Follow on LinkedIn for more content :- https://www.linkedin.com/in/manish-kumar-shah
๐ Follow on Instagram for Short Notes :- https://instagram.com/codes.m...โ
Thanks to the high frequency of updates (latest data received on 11 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.
38 617
Subscribers
-1624 hours
-1207 days
-58330 days
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Channel Posts
| 2 | Cybersecurity is no longer just a tech skill.
Itโs becoming a basic digital survival skill.
Almost everything today lives online:
โข Banking
โข Remote work
โข Social media
โข Cloud storage
โข AI tools
โข 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:
โข Weak passwords
โข Fake emails
โข Unsafe downloads
โข Poor security awareness
And with AI making scams more convincing, understanding cybersecurity fundamentals is becoming valuable across almost every profession, not just IT roles.
Thatโs one reason Iโve 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.
Whatโs one cybersecurity habit you think everyone should follow daily? | 10 324 |
| 3 |  No text... | 5 368 |
| 4 | https://www.instagram.com/reel/DYXMuIxS_Jv/?igsh=MXFmMjdlamNjYmV1Zw==
Google is hiring for 2026 Summer Interns | 3 277 |
| 5 | Google Summer Internship 2026 ๐ฅ
https://www.instagram.com/reel/DYXMuIxS_Jv/?igsh=MXFmMjdlamNjYmV1Zw== | 0 |
| 6 | Google Summer Internship 2026 ๐ฅ
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 youโre watching a long neural network video without properly understanding the basics behind it.
Thatโs where a lot of people get stuck.
Iโve 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:
โข Python for ML: https://imp.i384100.net/eKJOOZ
โข Data preprocessing: https://imp.i384100.net/Jk26Mq
โข Regression + classification: https://imp.i384100.net/g1KJEA
โข Supervised and unsupervised learning: https://imp.i384100.net/0GP6vR
โข Neural networks: https://imp.i384100.net/DKrLn2
โข 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.
Iโve 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? | 14 913 |
| 8 |  No text... | 2 844 |
| 9 | https://www.instagram.com/reel/DYR6ZLayelw/?igsh=d3hnazhuM3VuNHR0
HIRING REALITY 2026!๐ฎ
Do checks this out before your next Job switch. ๐ | 3 205 |
| 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 ๐ป๐คโ
First reel dropping soon๐๐
Do LIKE FOLLOW SHARE my page!
Need your immense support!๐๐๐ป๐ | 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:
โณ Start with basics like Python and data handling.
โณ Understand statistics and how data actually works.
โณ Learn core Machine Learning concepts.
โณ Build small real-world projects.
โณ 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 โน7,999 instead of โน13,999.
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 |  No text... | 0 |
| 13 | Most people trying to learn AI in 2026 are doing it wrong.
Hereโs the reality of learning AI today:
โณ Tools change every week
โณ Tutorials are fragmented
โณ Fundamentals are often skipped
The problem isnโt lack of content.
Itโs lack of structure
1. Start with tools first
โ OLD: Learn ChatGPT, agents, tools first
โ
NEW: Tools change fast. Fundamentals donโt
Understanding models, data, and workflows gives long-term leverage
2. Learn from random tutorials
โ OLD: YouTube + scattered resources are enough
โ
NEW: Random learning creates gaps
Structured paths across AI, ML, and Data Science compound better
3. Focus only on prompting
โ OLD: Prompting = AI mastery
โ
NEW: Prompting is just the interface
Real value comes from building systems
4. Consume more, build less
โ OLD: Keep learning before building
โ
NEW: Small projects teach faster than passive content
5. Learn AI in isolation
โ OLD: Just learn AI
โ
NEW: AI + Data + Product thinking is the real edge
What actually works:
โณ Structured learning paths
โณ Hands-on projects
โณ Layered skill building across domains
With how fast AI is evolving right now, unstructured learning just doesnโt 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 โน7,999 for a year (earlier โน13,999)
Click here to explore the Spring offer: https://imp.i384100.net/c/4788814/3812616/14726
AI isnโt just about using tools anymore.
Itโs about understanding and building with them.
Are you currently building AI projects or mostly consuming content? | 0 |
| 14 |  No text... | 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 |
