🚀 Want to build practical IT skills with Python?
The Google IT Automation with Python Professional Certificate is a great learning path for anyone looking to develop skills in:
Python programming
IT automation
Troubleshooting & IT support
Git & GitHub
Automating repetitive tasks
Practical IT workflows
Instructor: Google Career Certificates
998K+ learners already enrolled
The course is shown as “Enroll for free” and starts September 25.
If you're learning Python and want to move beyond basic coding into real-world automation, this is worth checking out.
👉 Enroll for free and start learning!
https://www.clcoding.com/2023/10/google-it-automation-with-python.html
The Google IT Automation with Python Professional Certificate is a great learning path for anyone looking to develop skills in:
Python programming
IT automation
Troubleshooting & IT support
Git & GitHub
Automating repetitive tasks
Practical IT workflows
Instructor: Google Career Certificates
998K+ learners already enrolled
The course is shown as “Enroll for free” and starts September 25.
If you're learning Python and want to move beyond basic coding into real-world automation, this is worth checking out.
👉 Enroll for free and start learning!
https://www.clcoding.com/2023/10/google-it-automation-with-python.html
❤1
🚀 Python Tip: Meet httpx — Async Web Requests Made Easy!
Need to work with APIs or fetch web data efficiently? httpx is a modern Python HTTP client that supports both synchronous and asynchronous requests.
https://gumroad.com/products/jsahj/
With httpx, you can:
Make API requests
Use async/await for concurrent requests
Work with JSON responses
Access REST APIs easily
Build faster data-fetching applications
Why learn httpx?
If you're building modern Python applications, web scrapers, API clients, or async applications, understanding httpx can be extremely useful.
Need to work with APIs or fetch web data efficiently? httpx is a modern Python HTTP client that supports both synchronous and asynchronous requests.
https://gumroad.com/products/jsahj/
With httpx, you can:
Make API requests
Use async/await for concurrent requests
Work with JSON responses
Access REST APIs easily
Build faster data-fetching applications
Why learn httpx?
If you're building modern Python applications, web scrapers, API clients, or async applications, understanding httpx can be extremely useful.
❤1
40+ FREE Python Books from Amazon!
Want to improve your Python skills without spending a fortune?
I found a collection of 40+ Python books available for free for a limited time — covering topics from Python fundamentals to programming, data science, automation, and more.
Perfect for:
✅ Python beginners
✅ Developers
✅ Data Science learners
✅ Students
✅ Interview preparation
✅ Anyone building a Python library
Limited-time offer — availability may change.
👉 Check the full list here:
https://www.clcoding.com/2025/03/free-40-python-books-from-amazon.html
Want to improve your Python skills without spending a fortune?
I found a collection of 40+ Python books available for free for a limited time — covering topics from Python fundamentals to programming, data science, automation, and more.
Perfect for:
✅ Python beginners
✅ Developers
✅ Data Science learners
✅ Students
✅ Interview preparation
✅ Anyone building a Python library
Limited-time offer — availability may change.
👉 Check the full list here:
https://www.clcoding.com/2025/03/free-40-python-books-from-amazon.html
❤1
Debugging in real life be like…
Senior Dev: “How did you fix that bug?”
Intern: “Commented the code.”
Senior Dev: “WHY DOES THAT EVEN WORK?! ”
Sometimes the code doesn’t need fixing…
It just needs you to stop touching it.
Projects: https://link.amazon/B0ibgjvpm
Senior Dev: “How did you fix that bug?”
Intern: “Commented the code.”
Senior Dev: “WHY DOES THAT EVEN WORK?! ”
Sometimes the code doesn’t need fixing…
It just needs you to stop touching it.
Projects: https://link.amazon/B0ibgjvpm
❤2👍1
Did you know Python’s pow() can do more than just calculate powers?
Projects: https://link.amazon/B09zAuCRQ
Python’s built-in pow() function has a powerful three-argument form:
The three-argument version is especially useful for modular arithmetic, cryptography, number theory, and competitive programming.
One small Python function, a surprisingly powerful feature.
Save this post—you might need it in an interview or coding challenge!
Projects: https://link.amazon/B09zAuCRQ
Python’s built-in pow() function has a powerful three-argument form:
The three-argument version is especially useful for modular arithmetic, cryptography, number theory, and competitive programming.
One small Python function, a surprisingly powerful feature.
Save this post—you might need it in an interview or coding challenge!
❤1
Python Coding Challenge — Day 1259
Can you predict the output without running the code?
A small Python snippet can hide a tricky concept!
Try it yourself first, then check the explanation:
https://www.clcoding.com/2026/09/python-coding-challenge-day-1259-what.html
Can you predict the output without running the code?
A small Python snippet can hide a tricky concept!
Try it yourself first, then check the explanation:
https://www.clcoding.com/2026/09/python-coding-challenge-day-1259-what.html
❤1
🌀 Turn Python noise into a procedural world!
What looks like a simple grid of characters is actually generated using Perlin noise — a technique commonly used to create natural-looking terrain, textures, clouds, landscapes, and procedural environments.
This Python example uses noise.pnoise2() to generate 2D noise and maps the values into different character intensities, creating an AI-like terrain visualization directly in the terminal.
✨ What’s happening here?
2D Perlin noise generates smooth random patterns
Values are converted into visual characters
Nested loops build the terrain row by row
The result resembles a procedural height map
All of it is generated with Python
The cool part: You don't need an image file or game engine to create interesting procedural visuals — Python can generate them from scratch.
💻 Python + Noise = Procedural Art
https://link.amazon/B09QnUQMf
What looks like a simple grid of characters is actually generated using Perlin noise — a technique commonly used to create natural-looking terrain, textures, clouds, landscapes, and procedural environments.
This Python example uses noise.pnoise2() to generate 2D noise and maps the values into different character intensities, creating an AI-like terrain visualization directly in the terminal.
✨ What’s happening here?
2D Perlin noise generates smooth random patterns
Values are converted into visual characters
Nested loops build the terrain row by row
The result resembles a procedural height map
All of it is generated with Python
The cool part: You don't need an image file or game engine to create interesting procedural visuals — Python can generate them from scratch.
💻 Python + Noise = Procedural Art
https://link.amazon/B09QnUQMf
❤1
Python Quiz Of the Day
Python Coding Challenge - Question with Answer (ID 260926)
Answer with Explanation: https://www.clcoding.com/2026/09/python-coding-challenge-id-260926.html
Python Coding Challenge - Question with Answer (ID 260926)
Answer with Explanation: https://www.clcoding.com/2026/09/python-coding-challenge-id-260926.html
❤1
Python developers will understand this pain!
Normal people using Python:
“I have a doubt.”
“Sure! Let me explain it step by step.”
Python developers at 3 AM:
“Where is the error?”
“Let me check again…”
“But it worked yesterday!”
https://link.amazon/B0el1x3VX
From learning Python, Pandas, Matplotlib and Data Analysis to hunting bugs in the middle of the night — every developer has been there.
The real Python developer journey is:
Learn → Practice → Build → Debug → Repeat → Grow
And somehow… that one missing bracket is always hiding where you least expect it.
Normal people using Python:
“I have a doubt.”
“Sure! Let me explain it step by step.”
Python developers at 3 AM:
“Where is the error?”
“Let me check again…”
“But it worked yesterday!”
https://link.amazon/B0el1x3VX
From learning Python, Pandas, Matplotlib and Data Analysis to hunting bugs in the middle of the night — every developer has been there.
The real Python developer journey is:
Learn → Practice → Build → Debug → Repeat → Grow
And somehow… that one missing bracket is always hiding where you least expect it.
❤1
ML Papers Explained — Free PDF Resource
Want to understand important Machine Learning research papers without getting overwhelmed?
This free resource, “ML Papers Explained,” can help you explore key ML concepts, research ideas, and influential papers in a more accessible way.
Perfect for:
• Machine Learning students
• AI & Data Science learners
• Researchers & developers
• Anyone interested in ML research
Get this FREE resource:
https://www.clcoding.com/2026/09/ml-papers-explained.html
Want to understand important Machine Learning research papers without getting overwhelmed?
This free resource, “ML Papers Explained,” can help you explore key ML concepts, research ideas, and influential papers in a more accessible way.
Perfect for:
• Machine Learning students
• AI & Data Science learners
• Researchers & developers
• Anyone interested in ML research
Get this FREE resource:
https://www.clcoding.com/2026/09/ml-papers-explained.html
❤1
Calculate Planet Positions with Python!
Ever wondered how to find where a planet is located in the sky using Python?
With the Skyfield library, you can calculate a planet’s:
Right Ascension (RA)
Declination (DEC)
Distance from Earth in AU
Projects: https://link.amazon/B0dCBEgvw
Ever wondered how to find where a planet is located in the sky using Python?
With the Skyfield library, you can calculate a planet’s:
Right Ascension (RA)
Declination (DEC)
Distance from Earth in AU
Projects: https://link.amazon/B0dCBEgvw
❤1
AI in Healthcare is transforming the future of medicine!
Interested in learning how Artificial Intelligence is being applied to healthcare? The AI in Healthcare Specialization from Stanford Online is a great opportunity to explore this rapidly growing field.
What makes it interesting?
Learn applications of AI in healthcare
Explore AI-driven healthcare technologies
Understand how data and machine learning support healthcare
Learn from instructors associated with Stanford
Join a growing global learning community
Enroll for FREE — Starts Sep 26
https://www.clcoding.com/2025/05/ai-in-healthcare-specialization.html
If you're interested in AI, healthcare, machine learning, or data science, this is a course worth checking out.
Interested in learning how Artificial Intelligence is being applied to healthcare? The AI in Healthcare Specialization from Stanford Online is a great opportunity to explore this rapidly growing field.
What makes it interesting?
Learn applications of AI in healthcare
Explore AI-driven healthcare technologies
Understand how data and machine learning support healthcare
Learn from instructors associated with Stanford
Join a growing global learning community
Enroll for FREE — Starts Sep 26
https://www.clcoding.com/2025/05/ai-in-healthcare-specialization.html
If you're interested in AI, healthcare, machine learning, or data science, this is a course worth checking out.
❤1
When the code in your head is simple… but the code you actually write becomes a whole debugging adventure.
Code in my mind:
for i in range(5):
print("Hello, World!")
Code I actually write:
Loops + conditions + overthinking + debugging + questioning every life decision.
And then finally…
THE OUTPUT:
Even: 0
Odd: 1
Even: 2
Odd: 3
Even: 4
Sometimes Python isn't difficult. We just make it difficult.
https://gumroad.com/products/eyevx/
Code in my mind:
for i in range(5):
print("Hello, World!")
Code I actually write:
Loops + conditions + overthinking + debugging + questioning every life decision.
And then finally…
THE OUTPUT:
Even: 0
Odd: 1
Even: 2
Odd: 3
Even: 4
Sometimes Python isn't difficult. We just make it difficult.
https://gumroad.com/products/eyevx/
❤1
Python Pattern Challenge — Day 14
Ready for another Python pattern challenge?
Day 14 is a great way to practice Python fundamentals while improving your understanding of nested loops, conditions, and pattern logic.
Don’t just look at the answer—try to predict the output and write the logic yourself!
Challenge: https://www.clcoding.com/2026/09/python-pattern-challenge-day-14.html
Ready for another Python pattern challenge?
Day 14 is a great way to practice Python fundamentals while improving your understanding of nested loops, conditions, and pattern logic.
Don’t just look at the answer—try to predict the output and write the logic yourself!
Challenge: https://www.clcoding.com/2026/09/python-pattern-challenge-day-14.html
❤1
Create a Radar Dashboard with Python!
Want to turn simple data into a visually engaging dashboard? This example uses Pygal to create a radar chart comparing AI models across multiple dimensions:
Speed
Accuracy
Vision
NLP
Reasoning
https://link.amazon/B03btqocF
The chart makes it easy to see where each model performs strongly and where there are differences between them.
The best part? You can generate the visualization directly in Jupyter Notebook using SVG rendering.
Python + Pygal = Interactive-looking data visualizations with just a few lines of code!
Try customizing the categories and values with your own dataset.
🔗 Source: clcoding.com
Want to turn simple data into a visually engaging dashboard? This example uses Pygal to create a radar chart comparing AI models across multiple dimensions:
Speed
Accuracy
Vision
NLP
Reasoning
https://link.amazon/B03btqocF
The chart makes it easy to see where each model performs strongly and where there are differences between them.
The best part? You can generate the visualization directly in Jupyter Notebook using SVG rendering.
Python + Pygal = Interactive-looking data visualizations with just a few lines of code!
Try customizing the categories and values with your own dataset.
🔗 Source: clcoding.com
❤1
25 GitHub Repositories Every Python Developer Should Know!
Want to improve your Python skills, discover powerful tools, and learn from real-world projects? GitHub is one of the best places to learn from the Python community.
👉 Explore the complete list:
https://www.clcoding.com/2025/02/25-github-repositories-every-python.html
Want to improve your Python skills, discover powerful tools, and learn from real-world projects? GitHub is one of the best places to learn from the Python community.
👉 Explore the complete list:
https://www.clcoding.com/2025/02/25-github-repositories-every-python.html
❤1
Daily Python Question — Day 1261
Can you predict the output of this Python code?
This challenge tests your understanding of new(), object creation, and how Python can control whether a new instance is created.
Code Explanation:
https://www.clcoding.com/2026/09/python-coding-challenge-day-1261-what.html
Can you predict the output of this Python code?
This challenge tests your understanding of new(), object creation, and how Python can control whether a new instance is created.
Code Explanation:
https://www.clcoding.com/2026/09/python-coding-challenge-day-1261-what.html
❤1
Python Quiz of the Day
Python Coding Challenge - Question with Answer (ID 270926)
Answer with Explanation: https://www.clcoding.com/2026/09/python-coding-challenge-id-270926.html
Python Coding Challenge - Question with Answer (ID 270926)
Answer with Explanation: https://www.clcoding.com/2026/09/python-coding-challenge-id-270926.html
❤1
LIVE SESSION ALERT — September Data Science Bootcamp!
We’re on Day 19 of the September Data Science Bootcamp, and today we’re diving into:
Complete EDA Workflow with a Real Dataset
In this live session, we’ll go beyond theory and work through a practical Exploratory Data Analysis (EDA) workflow, including:
📌 Understanding the dataset
📌 Data cleaning & preprocessing
📌 Handling missing values
📌 Exploring distributions & patterns
📌 Finding correlations & relationships
📌 Creating meaningful visualizations
📌 Extracting insights from real data
📌 Building a complete EDA workflow step-by-step
🎥 I’m going LIVE on YouTube — join the session FREE!
https://youtube.com/live/onPpGCnWHKc?feature=share
If you’re learning Python, Pandas, NumPy, Data Visualization, or Data Science, this is a great session to learn by actually working with data.
👉 Join the FREE live session and code along with me!
Day 19 — Complete EDA Workflow
Real Dataset | Practical Data Science | LIVE
We’re on Day 19 of the September Data Science Bootcamp, and today we’re diving into:
Complete EDA Workflow with a Real Dataset
In this live session, we’ll go beyond theory and work through a practical Exploratory Data Analysis (EDA) workflow, including:
📌 Understanding the dataset
📌 Data cleaning & preprocessing
📌 Handling missing values
📌 Exploring distributions & patterns
📌 Finding correlations & relationships
📌 Creating meaningful visualizations
📌 Extracting insights from real data
📌 Building a complete EDA workflow step-by-step
🎥 I’m going LIVE on YouTube — join the session FREE!
https://youtube.com/live/onPpGCnWHKc?feature=share
If you’re learning Python, Pandas, NumPy, Data Visualization, or Data Science, this is a great session to learn by actually working with data.
👉 Join the FREE live session and code along with me!
Day 19 — Complete EDA Workflow
Real Dataset | Practical Data Science | LIVE
❤2
The Little Book of Generative AI Foundations — FREE PDF
Want to understand the mathematical foundations behind Generative AI without getting lost in overly complex theory?
195 Pages
Intuitive mathematical explanations
Covers the foundations behind modern Generative AI
Great for AI, ML & Python learners
Useful for building a stronger understanding of how GenAI works
Get the FREE PDF:
https://www.clcoding.com/2026/09/the-little-book-of-generative-ai.html
Want to understand the mathematical foundations behind Generative AI without getting lost in overly complex theory?
195 Pages
Intuitive mathematical explanations
Covers the foundations behind modern Generative AI
Great for AI, ML & Python learners
Useful for building a stronger understanding of how GenAI works
Get the FREE PDF:
https://www.clcoding.com/2026/09/the-little-book-of-generative-ai.html
❤1