14 GitHub Profiles Every Python, Data Science & AI Developer Should Follow
Want to learn from real-world code, projects, libraries, research, and open-source contributions?
Here are 14 GitHub profiles worth exploring if you're building skills in:
Python
Data Science
AI & Machine Learning
Deep Learning
Open Source
Research & Engineering
Instead of only watching tutorials, explore how experienced developers and researchers actually build things on GitHub.
👉 Check out the full list here:
https://www.clcoding.com/2026/09/14-best-github-profiles-every-python.html
Want to learn from real-world code, projects, libraries, research, and open-source contributions?
Here are 14 GitHub profiles worth exploring if you're building skills in:
Python
Data Science
AI & Machine Learning
Deep Learning
Open Source
Research & Engineering
Instead of only watching tutorials, explore how experienced developers and researchers actually build things on GitHub.
👉 Check out the full list here:
https://www.clcoding.com/2026/09/14-best-github-profiles-every-python.html
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Python Quiz of the Day
Python Coding Challenge - Question with Answer (ID 280926)
Answer with Explanation: https://www.clcoding.com/2026/09/python-coding-challenge-id-280926.html
Python Coding Challenge - Question with Answer (ID 280926)
Answer with Explanation: https://www.clcoding.com/2026/09/python-coding-challenge-id-280926.html
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SEPTEMBER DATA SCIENCE BOOTCAMP — DAY 20 & 21
MACHINE LEARNING IS HERE!
We’re entering one of the most exciting phases of the September Data Science Bootcamp — Machine Learning!
Day 20 & Day 21
Topic: Machine Learning
LIVE on YouTube:
https://youtube.com/live/ncA5j_6qlXQ
In these sessions, we’ll explore:
• Machine Learning fundamentals
• Supervised & Unsupervised Learning
• Training & Testing Data
• Features & Targets
• Model Building
• Model Evaluation
• Practical Python examples
Join the LIVE session and learn Machine Learning step by step with Python.
MACHINE LEARNING IS HERE!
We’re entering one of the most exciting phases of the September Data Science Bootcamp — Machine Learning!
Day 20 & Day 21
Topic: Machine Learning
LIVE on YouTube:
https://youtube.com/live/ncA5j_6qlXQ
In these sessions, we’ll explore:
• Machine Learning fundamentals
• Supervised & Unsupervised Learning
• Training & Testing Data
• Features & Targets
• Model Building
• Model Evaluation
• Practical Python examples
Join the LIVE session and learn Machine Learning step by step with Python.
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Python Pattern Challenge — Day 15!
Ready for another pattern-building challenge?
Today's challenge is designed to sharpen your Python loops, nested loops, logic, and problem-solving skills.
👉 Try solving it yourself before checking the solution.
Challenge: https://www.clcoding.com/2026/09/python-pattern-challenge-day-15.html
Ready for another pattern-building challenge?
Today's challenge is designed to sharpen your Python loops, nested loops, logic, and problem-solving skills.
👉 Try solving it yourself before checking the solution.
Challenge: https://www.clcoding.com/2026/09/python-pattern-challenge-day-15.html
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Mastering Python for Artificial Intelligence
Want to build AI applications with Python?
This free 276-page PDF covers essential Python coding skills for Artificial Intelligence and helps you strengthen the programming foundation needed to work with advanced AI applications.
Download the Free PDF Book:
https://www.clcoding.com/2023/11/mastering-python-for-artificial.html
Want to build AI applications with Python?
This free 276-page PDF covers essential Python coding skills for Artificial Intelligence and helps you strengthen the programming foundation needed to work with advanced AI applications.
Download the Free PDF Book:
https://www.clcoding.com/2023/11/mastering-python-for-artificial.html
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Python Coding Challenge — Day 1266
Can you predict the output of this Python code without running it?
Test your Python knowledge, improve your problem-solving skills, and challenge yourself every day.
🔗 Check out Day 1266 and share your answer before checking the solution.
https://www.clcoding.com/2026/09/python-coding-challenge-day-1266-what.html
Can you predict the output of this Python code without running it?
Test your Python knowledge, improve your problem-solving skills, and challenge yourself every day.
🔗 Check out Day 1266 and share your answer before checking the solution.
https://www.clcoding.com/2026/09/python-coding-challenge-day-1266-what.html
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Learn Python from the University of Michigan — for FREE!
The Python for Everybody Specialization is a great opportunity to learn Python programming and data analysis, covering how to build programs, work with data, clean and analyze datasets, and visualize results.
University of Michigan
Instructor: Charles Russell Severance
2M+ learners enrolled
Enroll for free
If you're starting your Python journey or want to strengthen your fundamentals, this is a useful resource to explore.
👉 Enroll for free and start learning today!
https://www.clcoding.com/2023/11/python-for-everybody-specialization.html
The Python for Everybody Specialization is a great opportunity to learn Python programming and data analysis, covering how to build programs, work with data, clean and analyze datasets, and visualize results.
University of Michigan
Instructor: Charles Russell Severance
2M+ learners enrolled
Enroll for free
If you're starting your Python journey or want to strengthen your fundamentals, this is a useful resource to explore.
👉 Enroll for free and start learning today!
https://www.clcoding.com/2023/11/python-for-everybody-specialization.html
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September Data Science Bootcamp — Day 22
We’re reaching the final stage: Capstone Project!
In this session, we’ll bring everything together and work on an end-to-end Data Science project, covering:
• Data Collection
• Data Cleaning
• Exploratory Data Analysis (EDA)
• Model Building
• Evaluation & Insights
Real Data → Practice → Build → Complete
And the best part? You can join the session for FREE!
Learn by building a practical project and put your Python & Data Science skills into action.
Join the LIVE session and complete your Data Science journey!
https://youtube.com/live/WjPqBoaW4is
We’re reaching the final stage: Capstone Project!
In this session, we’ll bring everything together and work on an end-to-end Data Science project, covering:
• Data Collection
• Data Cleaning
• Exploratory Data Analysis (EDA)
• Model Building
• Evaluation & Insights
Real Data → Practice → Build → Complete
And the best part? You can join the session for FREE!
Learn by building a practical project and put your Python & Data Science skills into action.
Join the LIVE session and complete your Data Science journey!
https://youtube.com/live/WjPqBoaW4is
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Harvard University: CS50's Introduction to Cybersecurity
Learn the fundamentals of cybersecurity with Harvard University's CS50's Introduction to Cybersecurity.
This course is designed for both technical and non-technical learners and covers essential cybersecurity concepts in a beginner-friendly way.
5 weeks
Self-paced learning
2–6 hours per week
Free to enroll
Optional paid upgrade available
No prior cybersecurity experience required
A great free resource if you want to start learning cybersecurity, privacy, digital safety, and security fundamentals.
Start learning for free:
https://www.clcoding.com/2023/10/harvard-university-cs50s-introduction.html
Learn the fundamentals of cybersecurity with Harvard University's CS50's Introduction to Cybersecurity.
This course is designed for both technical and non-technical learners and covers essential cybersecurity concepts in a beginner-friendly way.
5 weeks
Self-paced learning
2–6 hours per week
Free to enroll
Optional paid upgrade available
No prior cybersecurity experience required
A great free resource if you want to start learning cybersecurity, privacy, digital safety, and security fundamentals.
Start learning for free:
https://www.clcoding.com/2023/10/harvard-university-cs50s-introduction.html
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Elementary Probability for Applications — Free PDF
Want to strengthen your probability and mathematical foundations?
This 163-page book introduces the fundamentals of probability with a focus on applications and practical understanding.
You’ll explore:
• Probability fundamentals
• Random variables
• Probability distributions
• Expected values
• Conditional probability
• Applications of probability
A useful resource for students, data science learners, AI/ML enthusiasts, and anyone building a strong mathematical foundation.
Free PDF available here:
https://www.clcoding.com/2026/07/elementary-probability-for-applications.html
Want to strengthen your probability and mathematical foundations?
This 163-page book introduces the fundamentals of probability with a focus on applications and practical understanding.
You’ll explore:
• Probability fundamentals
• Random variables
• Probability distributions
• Expected values
• Conditional probability
• Applications of probability
A useful resource for students, data science learners, AI/ML enthusiasts, and anyone building a strong mathematical foundation.
Free PDF available here:
https://www.clcoding.com/2026/07/elementary-probability-for-applications.html
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Did you know? Python has a neat way to represent hexadecimal numbers!
Hexadecimal is especially useful when working with colors, memory addresses, bitwise operations, and low-level programming.
https://link.amazon/B01B5f9zI
Hexadecimal is especially useful when working with colors, memory addresses, bitwise operations, and low-level programming.
https://link.amazon/B01B5f9zI
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Python Pattern Challenge — Day 16
Ready to sharpen your Python logic?
Today’s challenge focuses on pattern printing, a simple but powerful way to practice:
• Nested loops
• Logic building
• range()
• Spaces and formatting
• Problem-solving skills
Try solving it yourself before checking the solution.
Challenge: https://www.clcoding.com/2026/09/python-pattern-challenge-day-16.html
Ready to sharpen your Python logic?
Today’s challenge focuses on pattern printing, a simple but powerful way to practice:
• Nested loops
• Logic building
• range()
• Spaces and formatting
• Problem-solving skills
Try solving it yourself before checking the solution.
Challenge: https://www.clcoding.com/2026/09/python-pattern-challenge-day-16.html
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Graph Neural Networks for Molecular Discovery with Python is a 326-page resource focused on applying Graph Neural Networks (GNNs) to molecular discovery.
It covers topics such as:
Graph representation of molecules
Geometric deep learning
Molecular property prediction
Molecule generation
Python-based implementations
Applications of GNNs in drug and chemical discovery
Free PDF: https://www.clcoding.com/2026/07/graph-neural-networks-for-molecular.html#google_vignette
It covers topics such as:
Graph representation of molecules
Geometric deep learning
Molecular property prediction
Molecule generation
Python-based implementations
Applications of GNNs in drug and chemical discovery
Free PDF: https://www.clcoding.com/2026/07/graph-neural-networks-for-molecular.html#google_vignette
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Did you know? Every Python object has an identity.
In Python, you can use the built-in id() function to inspect an object's identity.
Both variables point to the same object, so they have the same identity.
Understanding object identity, references, and mutability is an important part of mastering Python.
Save this post if you're learning Python!
https://link.amazon/B0bmL31TF
In Python, you can use the built-in id() function to inspect an object's identity.
Both variables point to the same object, so they have the same identity.
Understanding object identity, references, and mutability is an important part of mastering Python.
Save this post if you're learning Python!
https://link.amazon/B0bmL31TF
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The Python learning journey in one picture!
Year 1: “Hello World!” — everything feels exciting.
Year 2: Data structures, OOP, DBMS, NumPy, Pandas… — now things get serious.
Year 3: “I wanna go home.” — because debugging, errors, and endless learning become part of the journey.
But honestly, becoming a good Python developer isn’t about knowing everything. It’s about building, breaking, debugging, and learning every day.
The real journey is messy — but that’s what makes it worth it.
https://link.amazon/B03IuCQ8v
Year 1: “Hello World!” — everything feels exciting.
Year 2: Data structures, OOP, DBMS, NumPy, Pandas… — now things get serious.
Year 3: “I wanna go home.” — because debugging, errors, and endless learning become part of the journey.
But honestly, becoming a good Python developer isn’t about knowing everything. It’s about building, breaking, debugging, and learning every day.
The real journey is messy — but that’s what makes it worth it.
https://link.amazon/B03IuCQ8v
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Python Quiz of the Day
Python Coding Challenge - Question with Answer (ID 011026)
Answer with Explanation: https://www.clcoding.com/2026/10/python-coding-challenge-id-011026.html
Python Coding Challenge - Question with Answer (ID 011026)
Answer with Explanation: https://www.clcoding.com/2026/10/python-coding-challenge-id-011026.html
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Turn your Python activity into a GitHub-style heatmap!
Want to visualize your coding consistency? This simple Python project uses Pandas, NumPy, and Calplot to create a GitHub-inspired activity heatmap.
You can:
Track daily Python activity
Visualize coding consistency
Spot your most active days
Build a yearly coding streak
Create beautiful activity dashboards
The best part? You can generate something like this with just a few lines of Python.
Code → Visualize → Track → Improve.
Would you use a heatmap to track your coding journey?
https://link.amazon/B0hzpi2Nr
Want to visualize your coding consistency? This simple Python project uses Pandas, NumPy, and Calplot to create a GitHub-inspired activity heatmap.
You can:
Track daily Python activity
Visualize coding consistency
Spot your most active days
Build a yearly coding streak
Create beautiful activity dashboards
The best part? You can generate something like this with just a few lines of Python.
Code → Visualize → Track → Improve.
Would you use a heatmap to track your coding journey?
https://link.amazon/B0hzpi2Nr
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September Data Science Bootcamp — Day 1 to Day 22
From Python fundamentals to Data Science, this 22-day journey covered the complete learning path step by step.
We started with:
→ Python Foundations
→ Data Structures & Functions
→ Advanced Python & OOP
→ NumPy
→ Pandas
→ Data Visualization
→ Statistics
→ Exploratory Data Analysis
→ Machine Learning
→ End-to-End Data Science Project
22 Days • 8 Phases • 1 Complete Data Science Journey 🚀
💻 Full Bootcamp Code List:
https://www.clcoding.com/2026/10/september-data-science-bootcamp-day-1.html
If you missed the live sessions, you can now go through the complete Day 1–Day 22 bootcamp and learn at your own pace.
From Python fundamentals to Data Science, this 22-day journey covered the complete learning path step by step.
We started with:
→ Python Foundations
→ Data Structures & Functions
→ Advanced Python & OOP
→ NumPy
→ Pandas
→ Data Visualization
→ Statistics
→ Exploratory Data Analysis
→ Machine Learning
→ End-to-End Data Science Project
22 Days • 8 Phases • 1 Complete Data Science Journey 🚀
💻 Full Bootcamp Code List:
https://www.clcoding.com/2026/10/september-data-science-bootcamp-day-1.html
If you missed the live sessions, you can now go through the complete Day 1–Day 22 bootcamp and learn at your own pace.
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Turn Any PDF into a Keyword Mind Map with Python!
Want to quickly understand what’s inside a PDF? You can use Python to extract the text, find the most common keywords, and turn them into a simple mind-map-style output.
The workflow uses:
PyMuPDF (fitz) — extract text from the PDF
Regex — identify words
Counter — find the most frequent keywords
A simple script can help you discover the key topics in a document without reading every page manually.
Perfect for:
Research papers
E-books & notes
Study materials
Documentation
Quick PDF analysis
Python makes working with documents surprisingly simple.
https://link.amazon/B01ALdoeB
Want to quickly understand what’s inside a PDF? You can use Python to extract the text, find the most common keywords, and turn them into a simple mind-map-style output.
The workflow uses:
PyMuPDF (fitz) — extract text from the PDF
Regex — identify words
Counter — find the most frequent keywords
A simple script can help you discover the key topics in a document without reading every page manually.
Perfect for:
Research papers
E-books & notes
Study materials
Documentation
Quick PDF analysis
Python makes working with documents surprisingly simple.
https://link.amazon/B01ALdoeB
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Python for Data Analysis — Free PDF
Want to take your Python skills into real-world data analysis?
This 905-page guide covers a wide range of topics around:
Python for Data Analysis
Data Analytics & Visualization
Advanced Models
Automation & Scalable Data Workflows
Practical tools and techniques for modern data work
A useful resource for Python developers, data analysts, and anyone building skills in data science.
Free PDF: https://www.clcoding.com/2026/07/python-for-data-analysis-modern-guide.html
Want to take your Python skills into real-world data analysis?
This 905-page guide covers a wide range of topics around:
Python for Data Analysis
Data Analytics & Visualization
Advanced Models
Automation & Scalable Data Workflows
Practical tools and techniques for modern data work
A useful resource for Python developers, data analysts, and anyone building skills in data science.
Free PDF: https://www.clcoding.com/2026/07/python-for-data-analysis-modern-guide.html
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