🩺 No Coding Background? You Can Still Build AI for Healthcare https://youtube.com/playlist?list=PL0nX4ZoMtjYGSy-rn7-JKt0XMwKBpxyoE&si=N8rHxnIYnZvF-WBz
Many people think AI in healthcare is only for programmers.
That’s not true.
If you can understand patient data, charts, or clinical reports, you can learn Python for Healthcare AI — even with zero coding experience.
We start from the basics:
Python from scratch (no assumptions)
Working with real healthcare datasets
Turning medical data into AI models step by step
No computer science degree required.
Just curiosity and the desire to solve real healthcare problems.
#PythonForBeginners #HealthcareAI #AIinMedicine #MedicalAI #HealthTech #DataScience #LearnPython
Many people think AI in healthcare is only for programmers.
That’s not true.
If you can understand patient data, charts, or clinical reports, you can learn Python for Healthcare AI — even with zero coding experience.
We start from the basics:
Python from scratch (no assumptions)
Working with real healthcare datasets
Turning medical data into AI models step by step
No computer science degree required.
Just curiosity and the desire to solve real healthcare problems.
#PythonForBeginners #HealthcareAI #AIinMedicine #MedicalAI #HealthTech #DataScience #LearnPython
👍4
𝐁𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐀𝐈 𝐟𝐨𝐫 𝐡𝐞𝐚𝐥𝐭𝐡𝐜𝐚𝐫𝐞 𝐢𝐬𝐧’𝐭 𝐣𝐮𝐬𝐭 𝐚𝐛𝐨𝐮𝐭 𝐦𝐨𝐝𝐞𝐥𝐬. https://youtu.be/SPlCXMcUvCg
It starts with how you structure patient data.
In this video, I explain Python classes and objects using a patient-based example — the same design thinking used in real healthcare AI systems.
What I cover:
➡️ How classes act as blueprints for patient records
➡️ Why self matters when working with multiple patients
➡️ How objects store validated medical data safely
➡️ Adding behavior like feature extraction inside a class
➡️ How patient objects flow into an ML pipeline
This is the same foundation behind libraries like pandas, scikit-learn, and PyTorch.
If you’re learning Python for AI in healthcare, this concept matters more than most people realize.
🎥 Watch here: https://youtu.be/SPlCXMcUvCg
#HealthcareAI #Python #MachineLearning #DataScience #OOP #AIEngineering
It starts with how you structure patient data.
In this video, I explain Python classes and objects using a patient-based example — the same design thinking used in real healthcare AI systems.
What I cover:
➡️ How classes act as blueprints for patient records
➡️ Why self matters when working with multiple patients
➡️ How objects store validated medical data safely
➡️ Adding behavior like feature extraction inside a class
➡️ How patient objects flow into an ML pipeline
This is the same foundation behind libraries like pandas, scikit-learn, and PyTorch.
If you’re learning Python for AI in healthcare, this concept matters more than most people realize.
🎥 Watch here: https://youtu.be/SPlCXMcUvCg
#HealthcareAI #Python #MachineLearning #DataScience #OOP #AIEngineering
YouTube
Python for Beginners: Classes and Objects for AI in Healthcare (with Live Coding)
Master Python Classes and Objects with this Healthcare AI tutorial!
🩺 Learn Python Object-Oriented Programming (OOP) from scratch by building a real-world Patient Management class. This beginner-friendly guide is perfect for anyone starting their Data Science…
🩺 Learn Python Object-Oriented Programming (OOP) from scratch by building a real-world Patient Management class. This beginner-friendly guide is perfect for anyone starting their Data Science…
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If you want to learn 𝐏𝐲𝐭𝐡𝐨𝐧 𝐟𝐨𝐫 𝐀𝐈 𝐢𝐧 𝐡𝐞𝐚𝐥𝐭𝐡𝐜𝐚𝐫𝐞 𝐟𝐫𝐨𝐦 𝐳𝐞𝐫𝐨, with real medical examples and clear thinking, now is the right time. https://youtube.com/playlist?list=PL0nX4ZoMtjYGSy-rn7-JKt0XMwKBpxyoE&si=N8rHxnIYnZvF-WBz
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Introduction to Prompt Engineering
https://www.youtube.com/watch?v=nAR8j34LfOo
https://www.youtube.com/watch?v=nAR8j34LfOo
YouTube
Prompt Engineering Course | Introduction to Generative AI
Unlock the core skills behind Generative AI and learn how to communicate with large language models with clarity and control. This video walks through the foundations of prompt engineering, from how modern AI systems work to the techniques that produce accurate…
👍3
Fundamentals of Prompt Construction
https://www.youtube.com/watch?v=HPJQUXjbXK8
https://www.youtube.com/watch?v=HPJQUXjbXK8
YouTube
Prompt Engineering Course | Fundamentals of Prompt Construction
Unlock the core skills behind Generative AI and learn how to communicate with large language models with clarity and control. This video walks through the foundations of prompt engineering, from how modern AI systems work to the techniques that produce accurate…
👍5
Anatomy of Effective prompts
https://www.youtube.com/watch?v=UNefQTS7TeE
https://www.youtube.com/watch?v=UNefQTS7TeE
YouTube
Prompt Engineering Course | Anatomy of Effective Prompting
Unlock the core skills behind Generative AI and learn how to communicate with large language models with clarity and control. This video walks through the foundations of prompt engineering, from how modern AI systems work to the techniques that produce accurate…
👍3❤1
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Demo: Predicting Heart Disease Risk
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Constructing Clear Prompt Instructions
https://youtu.be/dY4Bus9Er6Y
https://youtu.be/dY4Bus9Er6Y
YouTube
Prompt Engineering Course | Constructing Clear Instructions
Unlock the core skills behind Generative AI and learn how to communicate with large language models with clarity and control. This video walks through the foundations of prompt engineering, from how modern AI systems work to the techniques that produce accurate…
❤2
The core philosophy's of Golang vs Python
https://youtu.be/GiUCX5kDtc8
Join Go Dev Community @godevcommunity
https://youtu.be/GiUCX5kDtc8
Join Go Dev Community @godevcommunity
YouTube
Go for Python Developers – Day 1: Go Philosophy, Typing, Compilation & Tooling
Python developers often struggle with Go not because it’s hard, but because it follows a very different philosophy.
In this first lesson of our Python to Go professional learning series, we focus on understanding why Go exists and how its design choices…
In this first lesson of our Python to Go professional learning series, we focus on understanding why Go exists and how its design choices…
👍3
Why Go Beats Python for Scalable Machine Learning in Production
After years of building and deploying ML-powered applications, I have reached a clear conclusion.
https://medium.com/@epythonlab/why-go-beats-python-for-scalable-machine-learning-in-production-c5f91618be97
After years of building and deploying ML-powered applications, I have reached a clear conclusion.
https://medium.com/@epythonlab/why-go-beats-python-for-scalable-machine-learning-in-production-c5f91618be97
Medium
Why Go Beats Python for Scalable Machine Learning in Production
However, my view changes when we shift from training models to running them in production.
👍3
How to configure Go's Environment on VsCode
https://youtu.be/4ZGpEoCi-xs
https://youtu.be/4ZGpEoCi-xs
YouTube
Go Setup for Beginners (2026) | Install Go + VS Code + Essential Commands
In Day 2 of the Python to Go transition series, we fully set up a professional Go development environment from scratch.
You’ll learn how to install the Go compiler correctly, configure Visual Studio Code with the official Go extension, install required development…
You’ll learn how to install the Go compiler correctly, configure Visual Studio Code with the official Go extension, install required development…
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Every time I started a new machine learning project, I faced the same frustration.
Create folders.
Set up configs.
Prepare data directories.
Add logging.
Structure modules properly.
And before even writing the first model… I was already tired.
So I built a solution.
I created ScaffML — an automated ML project structure generator that sets up clean, scalable, production-ready machine learning architecture in seconds.
No messy folders.
No inconsistent structure.
No wasted setup time.
Just install: pip install scaffml
Generate your project, and focus on building models — not folders.
If you're working in ML, AI, or data-driven systems, this might save you more time than you think.
I’d love your feedback and suggestions to make it even better.
PyPi: https://pypi.org/project/scaffml/
Create folders.
Set up configs.
Prepare data directories.
Add logging.
Structure modules properly.
And before even writing the first model… I was already tired.
So I built a solution.
I created ScaffML — an automated ML project structure generator that sets up clean, scalable, production-ready machine learning architecture in seconds.
No messy folders.
No inconsistent structure.
No wasted setup time.
Just install: pip install scaffml
Generate your project, and focus on building models — not folders.
If you're working in ML, AI, or data-driven systems, this might save you more time than you think.
I’d love your feedback and suggestions to make it even better.
PyPi: https://pypi.org/project/scaffml/
👍6
In the last 24 hours, there have been 422 downloads of scaffml(Professional ML Project Structure Generator) on PyPi.
PyPi: https://pypi.org/project/scaffml/
PyPi: https://pypi.org/project/scaffml/
Forwarded from Go Developers Community
In golang, we declare variables like x := 3. Does this kind of declaration make Go dynamic typed? Why?
Anonymous Quiz
54%
Yes
46%
No
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Go Variables and Data Types Deep Dive | Zero Values & Type Inference vs Python
https://www.youtube.com/watch?v=gCr28avlsnk
https://www.youtube.com/watch?v=gCr28avlsnk
YouTube
Go Variables and Data Types Deep Dive | Zero Values & Type Inference vs Python
In Day 4 of the Python-to-Go transition series, we explore how Go handles variables and data types — one of the most important foundations of the language.
You’ll learn:
The difference between var and :=
Go’s core built-in types: int, float64, string,…
You’ll learn:
The difference between var and :=
Go’s core built-in types: int, float64, string,…
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