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Remote Cloud Engineer Jobs at Global Top Companies, March 2026, Apply Now - Trends
Remote Marketing & Digital Marketing Jobs at Global Top Companies
Remote Cloud Engineer Jobs, March 2026
Hiring Companies:
- Fingerprint, Canonical, Growe, Revvity, Quokka, Ubiminds, Pathward, Outlive, Freestar
Apply Here:
https://cutt.ly/ptPVVu81
More Remote Tech Jobs Here👇
https://t.me/jobsourceglobal
SHARE WITH YOUR FRIENDS🥳🥳
Hiring Companies:
- Fingerprint, Canonical, Growe, Revvity, Quokka, Ubiminds, Pathward, Outlive, Freestar
Apply Here:
https://cutt.ly/ptPVVu81
More Remote Tech Jobs Here👇
https://t.me/jobsourceglobal
SHARE WITH YOUR FRIENDS🥳🥳
Dear my fellow devs, If you’re aiming for a bigger stage, be ready for the challenge. Working smarter is essential—but sometimes you also have to outwork the problem.
Forwarded from Free Courses: Google | Microsoft | Udemy | Coursera | IBM | NVIDIA | LinkedIn Learning | MIT | Udemy Coupons & PDF Books
✅ Learn New Skills FREE 🔰
1. Web Development ➝
◀️ https://t.me/webdevresourcestp
2. CSS ➝
◀️ http://css-tricks.com
3. JavaScript ➝
◀️ https://t.me/javascriptresourcestp
4. React ➝
◀️ http://react-tutorial.app
5. Python for AI
◀️ https://deeplearning.ai/short-courses/ai-python-for-beginners/
6. Data Science & Data Engineering ➝
◀️ https://t.me/datascienceresourcestp
7. Python ➝
◀️ http://pythontutorial.net
8. SQL ➝
◀️ https://t.me/sqlresourcestp
9. Git and GitHub ➝
◀️ http://GitFluence.com
10. Backend Development
◀️ https://udacity.com/course/intro-to-backend--ud171
11. Mongo DB ➝
◀️ http://mongodb.com
12. Node JS ➝
◀️ http://nodejsera.com
13. Data Structure & Algorithms
◀️ https://t.me/techpsyche
14. C#➝
◀️ https://learn.microsoft.com/en-us/training/paths/get-started-c-sharp-part-1/
15. Machine Learning➝
◀️ https://t.me/mlresourcestp
16. Android & iOS Development➝
◀️ https://t.me/mobiledevresourcestp
17. Java
◀️ https://t.me/javaresourcestp
18. Product Design
◀️ https://t.me/designresourcestp
Like for more ❤️
ENJOY LEARNING👍👍
Join Our WhatsApp Channel:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
1. Web Development ➝
◀️ https://t.me/webdevresourcestp
2. CSS ➝
◀️ http://css-tricks.com
3. JavaScript ➝
◀️ https://t.me/javascriptresourcestp
4. React ➝
◀️ http://react-tutorial.app
5. Python for AI
◀️ https://deeplearning.ai/short-courses/ai-python-for-beginners/
6. Data Science & Data Engineering ➝
◀️ https://t.me/datascienceresourcestp
7. Python ➝
◀️ http://pythontutorial.net
8. SQL ➝
◀️ https://t.me/sqlresourcestp
9. Git and GitHub ➝
◀️ http://GitFluence.com
10. Backend Development
◀️ https://udacity.com/course/intro-to-backend--ud171
11. Mongo DB ➝
◀️ http://mongodb.com
12. Node JS ➝
◀️ http://nodejsera.com
13. Data Structure & Algorithms
◀️ https://t.me/techpsyche
14. C#➝
◀️ https://learn.microsoft.com/en-us/training/paths/get-started-c-sharp-part-1/
15. Machine Learning➝
◀️ https://t.me/mlresourcestp
16. Android & iOS Development➝
◀️ https://t.me/mobiledevresourcestp
17. Java
◀️ https://t.me/javaresourcestp
18. Product Design
◀️ https://t.me/designresourcestp
Like for more ❤️
ENJOY LEARNING👍👍
Join Our WhatsApp Channel:
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This is a very COMMON issue that I observe in the projects of aspiring candidates
They download a DATASET from Kaggle or any other website
Export it to a Data Analysis TOOL
And START the project with data cleaning
After cleaning the data, they PLUG it into a dashboard
In the dashboard, they put EVERY column into the visuals
Also they APPLY the filters of top bottom 10
Once done, they crack their KNUCKLES
And put this project in a list of SUCCESSFULLY completed projects
Over time, I have REVIEWED so many portfolio projects
And I see this ISSUES almost every time
When I go to their portfolio, for every project there is a DASHBOARD
But WHAT should I do after seeing a dashboard
What is it trying to SAY
What should I do after SEEING top or bottom 10 cities, states or products
Every dashboard lacks CONTEXT
And why NOT
Because they DON'T even know the business problem or problem statement
So the dashboard you created is of NO use
Your job is not just to create DASHBOARDS
Your job would be to create DASHBOARDS to take out important INSIGHTS
And from those insights, you will build RECOMMENDATIONS
And these recommendations will be given to stakeholders as a SOLUTION to their business problem
If they implemented your IDEAS and the problem gets solved
Now you can say your work is DONE
If you are SHOWING bottom 10 states, then what
You should write the INSIGHTS too
For example, the sales of North India zone are FALLING
The insights can be used like this
Delhi that used to be in TOP 5 states is now in the BOTTOM 10 states
And this might be the REASON why our North India sales are DROPPING so hard
This is just a RANDOM example showing how your charts become UNDERSTANDABLE
Well, everyone can EXTRACT insights from charts
Even a KID can do this after looking at the tallest and smallest bar
The real task is to give RECOMMENDATIONS to solve the BUSINESS problem
And I have NEVER seen this in anyone's portfolio
If you are doing this, then you are easily STANDING out in the crowd
In my PORTFOLIO, I used to keep business problem, insights, dashboard and recommendations
Even in the bullet point of projects in my resume, I included RECOMMENDATIONS
Now this is what you can call a STRONG portfolio
Because your analysis skills are the SAME as those used in the real life by a Data Analyst
7 Free Data Analytics Certification Courses👇
tinyurl.com/326exaw7
16 Useful websites to master data analytics👇
t.me/dataanalysisresourcestp/212
Like if it helps 😄
Find More Tips & Resources Here:
whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
They download a DATASET from Kaggle or any other website
Export it to a Data Analysis TOOL
And START the project with data cleaning
After cleaning the data, they PLUG it into a dashboard
In the dashboard, they put EVERY column into the visuals
Also they APPLY the filters of top bottom 10
Once done, they crack their KNUCKLES
And put this project in a list of SUCCESSFULLY completed projects
Over time, I have REVIEWED so many portfolio projects
And I see this ISSUES almost every time
When I go to their portfolio, for every project there is a DASHBOARD
But WHAT should I do after seeing a dashboard
What is it trying to SAY
What should I do after SEEING top or bottom 10 cities, states or products
Every dashboard lacks CONTEXT
And why NOT
Because they DON'T even know the business problem or problem statement
So the dashboard you created is of NO use
Your job is not just to create DASHBOARDS
Your job would be to create DASHBOARDS to take out important INSIGHTS
And from those insights, you will build RECOMMENDATIONS
And these recommendations will be given to stakeholders as a SOLUTION to their business problem
If they implemented your IDEAS and the problem gets solved
Now you can say your work is DONE
If you are SHOWING bottom 10 states, then what
You should write the INSIGHTS too
For example, the sales of North India zone are FALLING
The insights can be used like this
Delhi that used to be in TOP 5 states is now in the BOTTOM 10 states
And this might be the REASON why our North India sales are DROPPING so hard
This is just a RANDOM example showing how your charts become UNDERSTANDABLE
Well, everyone can EXTRACT insights from charts
Even a KID can do this after looking at the tallest and smallest bar
The real task is to give RECOMMENDATIONS to solve the BUSINESS problem
And I have NEVER seen this in anyone's portfolio
If you are doing this, then you are easily STANDING out in the crowd
In my PORTFOLIO, I used to keep business problem, insights, dashboard and recommendations
Even in the bullet point of projects in my resume, I included RECOMMENDATIONS
Now this is what you can call a STRONG portfolio
Because your analysis skills are the SAME as those used in the real life by a Data Analyst
7 Free Data Analytics Certification Courses👇
tinyurl.com/326exaw7
16 Useful websites to master data analytics👇
t.me/dataanalysisresourcestp/212
Like if it helps 😄
Find More Tips & Resources Here:
whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
Forwarded from Intercom University
NVIDIA FREE AI Courses 🚀💻
Transform your skills with these cutting-edge courses by NVIDIA.
Check out the following NVIDIA FREE AI Certification Courses
Link👇:-
https://intercomuniversity.com/free-courses/nvidia-is-offering-6-ai-llm-courses-for-free/
Enroll For FREE & Get Certified 🎓
Transform your skills with these cutting-edge courses by NVIDIA.
Check out the following NVIDIA FREE AI Certification Courses
Link👇:-
https://intercomuniversity.com/free-courses/nvidia-is-offering-6-ai-llm-courses-for-free/
Enroll For FREE & Get Certified 🎓
Tim Cook stepping down as Apple CEO, John Ternus taking over
Apple announced that Tim Cook will step down as CEO on September 1, 2026, ending a 15-year tenure that began after Steve Jobs. He will transition to executive chairman, remaining involved in strategy and global policy. John Ternus, currently head of hardware engineering, will take over as CEO as part of a long-planned succession.
During Cook’s leadership, Apple grew dramatically—from a company worth about $350 billion to over $4 trillion—while expanding its product lineup with devices like the Apple Watch and AirPods and building a massive services business.
However, his tenure also faced challenges, including missteps like Apple Maps and slower progress in artificial intelligence.
Ternus, a longtime insider and key figure in Apple’s hardware development, is expected to lead the company into its next phase, particularly as it navigates increasing competition and the growing importance of AI.
🔆 t.me/techpsyche
Apple announced that Tim Cook will step down as CEO on September 1, 2026, ending a 15-year tenure that began after Steve Jobs. He will transition to executive chairman, remaining involved in strategy and global policy. John Ternus, currently head of hardware engineering, will take over as CEO as part of a long-planned succession.
During Cook’s leadership, Apple grew dramatically—from a company worth about $350 billion to over $4 trillion—while expanding its product lineup with devices like the Apple Watch and AirPods and building a massive services business.
However, his tenure also faced challenges, including missteps like Apple Maps and slower progress in artificial intelligence.
Ternus, a longtime insider and key figure in Apple’s hardware development, is expected to lead the company into its next phase, particularly as it navigates increasing competition and the growing importance of AI.
🔆 t.me/techpsyche
By the way, don’t be too hard on yourself. You might not have secured a remote job or landed that big opportunity yet, but think about how far you’ve come to reach your current stage, it’s no small thing. For me, the steps I’ve taken matter more than anything else. And honestly, they’ve already paid off in many ways. What truly matters now is to keep making continuous improvements.
❤1
PHP is said to be dead or dying soon. But it is not even sick enough to die😊
Forwarded from Crypto Stract | Web 3, Finance, Business, Blockchain, Crypto, Growth, Stock Market, Money
Tips to help you be successful:
* Implement healthy habits every day
Good habits are the foundation of wealth. They distinguish a successful wealthy person from a loser. In the latter, bad habits prevail. Think about what's stopping you? Awareness is the first step to change.
* Set goals regularly
Successful people are driven by their goals. There are always unconquered peaks in front of them. They plan their day in detail.
* Identify root causes
If you know why you want to achieve wealth and success, you will get there faster. Setting goals is important. But even more important is why you chose this particular goal.
* Get things done
The truth is as old as the world: do not put off until tomorrow what you can do today. Everyone has fears “What if it doesn’t work out?”, “It’s too difficult,” and so on. But successful people overcome them and bring important things to the end, no matter what it takes.
* Do the maximum and even a little more
To do something, if only to quickly and if only to lag behind - the approach of losers. Successful and wealthy people always do even a little more than what is required of them. If you have to stay at work for this - no problem! Putting in more effort is easy!
Entrepreneurs cheat sheet
t.me/cryptostract/125
How I keep my Finances Organized
t.me/cryptostract/147
More Resources Here:
whatsapp.com/channel/0029VajB00n0LKZ7cSloGR1M
* Implement healthy habits every day
Good habits are the foundation of wealth. They distinguish a successful wealthy person from a loser. In the latter, bad habits prevail. Think about what's stopping you? Awareness is the first step to change.
* Set goals regularly
Successful people are driven by their goals. There are always unconquered peaks in front of them. They plan their day in detail.
* Identify root causes
If you know why you want to achieve wealth and success, you will get there faster. Setting goals is important. But even more important is why you chose this particular goal.
* Get things done
The truth is as old as the world: do not put off until tomorrow what you can do today. Everyone has fears “What if it doesn’t work out?”, “It’s too difficult,” and so on. But successful people overcome them and bring important things to the end, no matter what it takes.
* Do the maximum and even a little more
To do something, if only to quickly and if only to lag behind - the approach of losers. Successful and wealthy people always do even a little more than what is required of them. If you have to stay at work for this - no problem! Putting in more effort is easy!
Entrepreneurs cheat sheet
t.me/cryptostract/125
How I keep my Finances Organized
t.me/cryptostract/147
More Resources Here:
whatsapp.com/channel/0029VajB00n0LKZ7cSloGR1M
👍1
Complete Data Science Roadmap 👇👇
1. Introduction to Data Science
- Overview and Importance
- Data Science Lifecycle
- Key Roles (Data Scientist, Analyst, Engineer)
2. Mathematics and Statistics
- Probability and Distributions
- Descriptive/Inferential Statistics
- Hypothesis Testing
- Linear Algebra and Calculus Basics
3. Programming Languages
- Python: NumPy, Pandas, Matplotlib
- R: dplyr, ggplot2
- SQL: Joins, Aggregations, CRUD
4. Data Collection & Preprocessing
- Data Cleaning and Wrangling
- Handling Missing Data
- Feature Engineering
5. Exploratory Data Analysis (EDA)
- Summary Statistics
- Data Visualization (Histograms, Box Plots, Correlation)
6. Machine Learning
- Supervised (Linear/Logistic Regression, Decision Trees)
- Unsupervised (K-Means, PCA)
- Model Selection and Cross-Validation
7. Advanced Machine Learning
- SVM, Random Forests, Boosting
- Neural Networks Basics
8. Deep Learning
- Neural Networks Architecture
- CNNs for Image Data
- RNNs for Sequential Data
9. Natural Language Processing (NLP)
- Text Preprocessing
- Sentiment Analysis
- Word Embeddings (Word2Vec)
10. Data Visualization & Storytelling
- Dashboards (Tableau, Power BI)
- Telling Stories with Data
11. Model Deployment
- Deploy with Flask or Django
- Monitoring and Retraining Models
12. Big Data & Cloud
- Introduction to Hadoop, Spark
- Cloud Tools (AWS, Google Cloud)
13. Data Engineering Basics
- ETL Pipelines
- Data Warehousing (Redshift, BigQuery)
14. Ethics in Data Science
- Ethical Data Usage
- Bias in AI Models
15. Tools for Data Science
- Jupyter, Git, Docker
16. Career Path & Certifications
- Building a Data Science Portfolio
Learn DatA & AI: https://365datascience.pxf.io/Z6KDgk
Free Notes & Books to learn Data Science: https://t.me/datascienceresourcestp
Python Project Ideas: https://t.me/pythonresourcestp/74
Best Resources to learn Data Science 👇👇
Python Tutorial (http://pythontutorial.net/)
Data Science Course (http://kaggle.com/learn) by Kaggle
Machine Learning Course (http://developers.google.com/machine-learning/crash-course) by Google
Best Data Science & Machine Learning Resources (https://topmate.io/learning_resources/1406977)
Interview Process for Data Science Role at Amazon (https://t.me/datascienceresourcestp/85)
Python Interview Resources (https://t.me/pythonresourcestp/40)
Join for more free courses
https://t.me/techpsyche
Like for more ❤️
ENJOY LEARNING👍👍
Join Our WhatsApp Channel:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
1. Introduction to Data Science
- Overview and Importance
- Data Science Lifecycle
- Key Roles (Data Scientist, Analyst, Engineer)
2. Mathematics and Statistics
- Probability and Distributions
- Descriptive/Inferential Statistics
- Hypothesis Testing
- Linear Algebra and Calculus Basics
3. Programming Languages
- Python: NumPy, Pandas, Matplotlib
- R: dplyr, ggplot2
- SQL: Joins, Aggregations, CRUD
4. Data Collection & Preprocessing
- Data Cleaning and Wrangling
- Handling Missing Data
- Feature Engineering
5. Exploratory Data Analysis (EDA)
- Summary Statistics
- Data Visualization (Histograms, Box Plots, Correlation)
6. Machine Learning
- Supervised (Linear/Logistic Regression, Decision Trees)
- Unsupervised (K-Means, PCA)
- Model Selection and Cross-Validation
7. Advanced Machine Learning
- SVM, Random Forests, Boosting
- Neural Networks Basics
8. Deep Learning
- Neural Networks Architecture
- CNNs for Image Data
- RNNs for Sequential Data
9. Natural Language Processing (NLP)
- Text Preprocessing
- Sentiment Analysis
- Word Embeddings (Word2Vec)
10. Data Visualization & Storytelling
- Dashboards (Tableau, Power BI)
- Telling Stories with Data
11. Model Deployment
- Deploy with Flask or Django
- Monitoring and Retraining Models
12. Big Data & Cloud
- Introduction to Hadoop, Spark
- Cloud Tools (AWS, Google Cloud)
13. Data Engineering Basics
- ETL Pipelines
- Data Warehousing (Redshift, BigQuery)
14. Ethics in Data Science
- Ethical Data Usage
- Bias in AI Models
15. Tools for Data Science
- Jupyter, Git, Docker
16. Career Path & Certifications
- Building a Data Science Portfolio
Learn DatA & AI: https://365datascience.pxf.io/Z6KDgk
Free Notes & Books to learn Data Science: https://t.me/datascienceresourcestp
Python Project Ideas: https://t.me/pythonresourcestp/74
Best Resources to learn Data Science 👇👇
Python Tutorial (http://pythontutorial.net/)
Data Science Course (http://kaggle.com/learn) by Kaggle
Machine Learning Course (http://developers.google.com/machine-learning/crash-course) by Google
Best Data Science & Machine Learning Resources (https://topmate.io/learning_resources/1406977)
Interview Process for Data Science Role at Amazon (https://t.me/datascienceresourcestp/85)
Python Interview Resources (https://t.me/pythonresourcestp/40)
Join for more free courses
https://t.me/techpsyche
Like for more ❤️
ENJOY LEARNING👍👍
Join Our WhatsApp Channel:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
Forwarded from Remote Chrome | RemoteChrome.com | Remote Jobs
♻️ Remote AI, ML Jobs to Apply in April 2026
Apply Here:
https://remotechrome.com/remotejobs/top-13-remote-ai-ml-jobs-to-apply-in-april-2026/
More Remote Tech Jobs Here👇
https://t.me/remotechrome
SHARE WITH YOUR FRIENDS🥳🥳
Apply Here:
https://remotechrome.com/remotejobs/top-13-remote-ai-ml-jobs-to-apply-in-april-2026/
More Remote Tech Jobs Here👇
https://t.me/remotechrome
SHARE WITH YOUR FRIENDS🥳🥳
Forwarded from Product Design Resources TP . UX Design . Graphic Design . Video Editing . 2D 3D Animation
5 Awesome tools for Web Designers
🎨 Color Hunt (https://colorhunt.co/)
🎨 Cool Backgrounds (https://coolbackgrounds.io/)
🎨 99 Designs (https://99designs.com/categories)
🎨 UI Design Tips (https://t.me/designresourcestp)
🎨 Gravit Designer (https://www.designer.io/en/)
🎨 Color Hunt (https://colorhunt.co/)
🎨 Cool Backgrounds (https://coolbackgrounds.io/)
🎨 99 Designs (https://99designs.com/categories)
🎨 UI Design Tips (https://t.me/designresourcestp)
🎨 Gravit Designer (https://www.designer.io/en/)
Forwarded from Crypto Stract | Web 3, Finance, Business, Blockchain, Crypto, Growth, Stock Market, Money
What is funding in crypto trading? 💸
In cryptocurrencies, funding refers to the funding rate that is redistributed among traders holding positions in perpetual futures.
Funding is a periodic payment/write-off for traders with open positions in perpetual futures, which allows them to compensate for the long-term difference between the price of the underlying asset and the derivative contract.
The need for funding arose from the idea of perpetual futures, which have no maturity and can be held indefinitely. Therefore, to compensate for the difference in the price of the asset and the contract, a financing rate mechanism was launched.
Non-Recourse Loans in Crypto: t.me/cryptostract/151
Signs of Bearish Trend in Crypto: t.me/cryptostract/152
Cryptocurrency Investing: t.me/cryptostract/153
Liquidity: t.me/cryptostract/154
More Resources Here:
https://whatsapp.com/channel/0029VajB00n0LKZ7cSloGR1M
In cryptocurrencies, funding refers to the funding rate that is redistributed among traders holding positions in perpetual futures.
Funding is a periodic payment/write-off for traders with open positions in perpetual futures, which allows them to compensate for the long-term difference between the price of the underlying asset and the derivative contract.
The need for funding arose from the idea of perpetual futures, which have no maturity and can be held indefinitely. Therefore, to compensate for the difference in the price of the asset and the contract, a financing rate mechanism was launched.
Non-Recourse Loans in Crypto: t.me/cryptostract/151
Signs of Bearish Trend in Crypto: t.me/cryptostract/152
Cryptocurrency Investing: t.me/cryptostract/153
Liquidity: t.me/cryptostract/154
More Resources Here:
https://whatsapp.com/channel/0029VajB00n0LKZ7cSloGR1M
Forwarded from Mobile Dev Resources . Android . iOS . Flutter . Kotlin . Swift . Java . React Native
🚀Kotlin Multiplatform, Compose Multiplatform
Let's take a look at the future of cross-platform development...
These are now serious trends in the world of mobile and cross-platform development. You may be wondering: "What are they? How are they different from Flutter or React Native? Can we bring our projects to them? What will their future be?"
Let's take a step-by-step look at them.
🔧 What is Kotlin Multiplatform (KMP)?
To put it very simply:
Instead of coding for Android with Kotlin, for iOS with Swift, for the Backend with Java or NodeJS, and writing everything separately again, you write business logic (app logic, database, API call, validation, data model, etc.) only once with Kotlin and share it across all platforms.
🎯 What does that mean?
On Android → you use the same Kotlin code.
On iOS → that code becomes a library usable for Swift.
You can even use the same logic for Desktop and Web.
✅ KMP Benefits
🔄 Gradual migration, you don't have to build the project from scratch, you can gradually add shared modules.
⚡️ Native performance, because you write the UI separately for each platform, the speed and feel are completely native.
👨💻 One language for everywhere, especially great for Android, because they work with the same Kotlin.
🛠Easy implementation and integration, KMP fits easily in the middle of existing projects (Enterprise and Startup).
🎨 What is Compose Multiplatform (CMP)?
Well, KMP shares the logic, but the UI is still separate. This is where Compose Multiplatform comes in.
And CMP is actually the multiplatform version of Jetpack Compose. With it, you can write your UI once and run it on:
Android
iOS (now stable 🎉)
Desktop (Windows, macOS, Linux)
Web (WASM)
✅ Benefits of CMP
🖼 Common UI for everywhere Write once, use everywhere.
🚀 Excellent performance and close to native
It is 100% native on Android.
It is now stable on iOS (since version 1.8.0) and provides a user experience exactly like SwiftUI (scrolls, drag&drop, text selection, adaptive UI, etc.).
It is also stable and very useful on Desktop (JetBrains itself wrote its products with it).
🧩 Gradual integration with UIKit/SwiftUI means you can work hybrid and gradually migrate UIs.
💪 Official support from JetBrains and Google means it is future-proof and serious.
⚖️ Comparison with Flutter and React Native
The Flutter framework is very fast and good for shared UI, but the UI is completely custom and runs on its own engine (Skia), meaning it is not native.
The React Native framework
The UI is written in JavaScript/TypeScript and connected to native with Bridge, which may sometimes cause performance issues.
The KMP + CMP frameworks share both logic and UI, and you always have full access to native APIs.
🔮 The future of KMP and CMP
Well, KMP is already used in large companies like Netflix and CashApp.
And CMP is now completely stable for Android, Desktop, and iOS, and the Web is also growing rapidly.
JetBrains has built its own apps and tools with CMP, meaning it has full faith in its future.
The combination of these two technologies (KMP + CMP) is really becoming a complete stack for developing Enterprise and Startup applications.
Flutter vs. React Native: t.me/mobiledevresourcestp/95
What makes an app actually work?: t.me/mobiledevresourcestp/121
Join Our WhatsApp Channel:
whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
Let's take a look at the future of cross-platform development...
These are now serious trends in the world of mobile and cross-platform development. You may be wondering: "What are they? How are they different from Flutter or React Native? Can we bring our projects to them? What will their future be?"
Let's take a step-by-step look at them.
🔧 What is Kotlin Multiplatform (KMP)?
To put it very simply:
Instead of coding for Android with Kotlin, for iOS with Swift, for the Backend with Java or NodeJS, and writing everything separately again, you write business logic (app logic, database, API call, validation, data model, etc.) only once with Kotlin and share it across all platforms.
🎯 What does that mean?
On Android → you use the same Kotlin code.
On iOS → that code becomes a library usable for Swift.
You can even use the same logic for Desktop and Web.
✅ KMP Benefits
🔄 Gradual migration, you don't have to build the project from scratch, you can gradually add shared modules.
⚡️ Native performance, because you write the UI separately for each platform, the speed and feel are completely native.
👨💻 One language for everywhere, especially great for Android, because they work with the same Kotlin.
🛠Easy implementation and integration, KMP fits easily in the middle of existing projects (Enterprise and Startup).
🎨 What is Compose Multiplatform (CMP)?
Well, KMP shares the logic, but the UI is still separate. This is where Compose Multiplatform comes in.
And CMP is actually the multiplatform version of Jetpack Compose. With it, you can write your UI once and run it on:
Android
iOS (now stable 🎉)
Desktop (Windows, macOS, Linux)
Web (WASM)
✅ Benefits of CMP
🖼 Common UI for everywhere Write once, use everywhere.
🚀 Excellent performance and close to native
It is 100% native on Android.
It is now stable on iOS (since version 1.8.0) and provides a user experience exactly like SwiftUI (scrolls, drag&drop, text selection, adaptive UI, etc.).
It is also stable and very useful on Desktop (JetBrains itself wrote its products with it).
🧩 Gradual integration with UIKit/SwiftUI means you can work hybrid and gradually migrate UIs.
💪 Official support from JetBrains and Google means it is future-proof and serious.
⚖️ Comparison with Flutter and React Native
The Flutter framework is very fast and good for shared UI, but the UI is completely custom and runs on its own engine (Skia), meaning it is not native.
The React Native framework
The UI is written in JavaScript/TypeScript and connected to native with Bridge, which may sometimes cause performance issues.
The KMP + CMP frameworks share both logic and UI, and you always have full access to native APIs.
🔮 The future of KMP and CMP
Well, KMP is already used in large companies like Netflix and CashApp.
And CMP is now completely stable for Android, Desktop, and iOS, and the Web is also growing rapidly.
JetBrains has built its own apps and tools with CMP, meaning it has full faith in its future.
The combination of these two technologies (KMP + CMP) is really becoming a complete stack for developing Enterprise and Startup applications.
Flutter vs. React Native: t.me/mobiledevresourcestp/95
What makes an app actually work?: t.me/mobiledevresourcestp/121
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