I would like to invite someone who are working as a Python developer and willing to share his/her experience for others as a question and answer. Just message to @ruthas.
Top 3 Python Mistakes Beginners Make (and How to Avoid Them)
https://youtu.be/vhG2GNZ4Bc8
https://youtu.be/vhG2GNZ4Bc8
YouTube
Top 3 Python Mistakes Beginners Make (and How to Avoid Them)
This video explores the top 3 common mistakes that Python beginners often encounter and provides practical solutions to avoid them. Whether you're new to programming or looking to refine your Python skills, understanding these pitfalls is crucial for your…
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15 𝘽𝙚𝙨𝙩 𝙋𝙮𝙩𝙝𝙤𝙣 𝘼𝙄/ 𝙈𝙖𝙘𝙝𝙞𝙣𝙚 𝙇𝙚𝙖𝙧𝙣𝙞𝙣𝙜 𝙋𝙧𝙤𝙟𝙚𝙘𝙩𝙨 𝙩𝙤 𝘽𝙤𝙤𝙨𝙩 𝙔𝙤𝙪𝙧 𝙎𝙠𝙞𝙡𝙡𝙨 https://medium.com/p/96677345b57d
Medium
Best Python Machine Learning Projects to Boost Your Skills
JOIN FOR MORE RESOURCES
Top 10 Pandas Functions to Filter Data Like a Pro (Step-by-Step Guide)
https://medium.com/@epythonlab/top-10-pandas-functions-to-filter-data-like-a-pro-step-by-step-guide-536ac28cac7a
https://medium.com/@epythonlab/top-10-pandas-functions-to-filter-data-like-a-pro-step-by-step-guide-536ac28cac7a
Medium
Top 10 Pandas Functions to Filter Data Like a Pro (Step-by-Step Guide)
Filtering data is one of the most crucial tasks in any data analysis process, especially when using pandas, Python’s most popular data…
Linear Algera is the backbone of machine learning https://youtu.be/BNa2s6OtWls
YouTube
Linear Algebra in Python with SciPy and NumPy: Step by Step
In this video, you will learn how to use SciPy and NumPy to solve problems related to vectors, matrices, eigenvalues, eigenvectors, and linear equations.
Chapters:
0:00 Day 1: Solve vectors with SciPy
7:39 Day 2: Solve Matrices with SciPy
21:55 Day 3: Solve…
Chapters:
0:00 Day 1: Solve vectors with SciPy
7:39 Day 2: Solve Matrices with SciPy
21:55 Day 3: Solve…
Step-by-step guide to code debugging in VSCode
https://www.youtube.com/watch?v=cJFYnHtEy1M
https://www.youtube.com/watch?v=cJFYnHtEy1M
YouTube
Step-by-Step Guide to Debugging in VS Code
Debugging Python code effectively involves understanding the tools and techniques that can help you identify and fix issues. Using the built-in debugger in VS Code is a powerful way to accomplish this. Below is a guide on how to use the VS Code debugger to…
❤3
Python Automation: Automatic File Organization https://youtu.be/JN-7zhAUbA4
YouTube
Python Automation: Automatic File Organization Script
Python automation tutorial. In this tutorial, you will learn and understand the logic behind python automation task.
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💰Donate to us at https://donorbox.org/donate-epythonlab…
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💰Donate to us at https://donorbox.org/donate-epythonlab…
❤2👍2
How to schedule python scripts to run automatically while you sleep https://www.youtube.com/watch?v=Stnuexbck7E
YouTube
How to Schedule Python Scripts to Run Automatically | Python Automation
🚀 Want to automate tasks using Python? In this tutorial, you’ll learn how to schedule Python scripts to run automatically using three different methods:
✅ Using the schedule Library – Best for simple automation within Python
✅ Using Windows Task Scheduler…
✅ Using the schedule Library – Best for simple automation within Python
✅ Using Windows Task Scheduler…
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Learn how to handle errors with exception handling in python
https://youtu.be/x1lLqux9Bmo
https://youtu.be/x1lLqux9Bmo
YouTube
Python for Beginners - Errors and Exception Handling
Welcome to Day 4 of the Python for Beginners tutorial. In this tutorial, you will learn the types of errors and exception handling in Python.
If you missed the previous day's tutorial, take a look at the playlist of this link
https://www.youtube.com/pla…
If you missed the previous day's tutorial, take a look at the playlist of this link
https://www.youtube.com/pla…
🎉2
Why Learning to Code is Essential for Understanding AI
Artificial intelligence (AI) is rapidly changing the world around us. From the devices we use to the way we interact with businesses, AI is becoming an integral part of our lives. As AI continues to evolve, it's essential to have a basic understanding of how it works. One of the best ways to do this is to learn to code.
Coding is the language of computers. By learning to code, you'll gain a better understanding of how computers work and how they can be used to create AI applications. You'll also learn how to think algorithmically, which is a valuable skill for problem-solving in general.
👉How to get started Python: https://www.youtube.com/watch?v=EGdhnSEWKok
👉Beginner's Guide to Python Programming. Getting started now: https://youtu.be/ISv6XIl1hn0
👉Data Structures with Projects full tutorial for beginners
https://www.youtube.com/watch?v=lbdKQI8Jsok
👉OOP in Python - beginners Crash Course https://www.youtube.com/watch?v=I7z6i1QTdsw
Artificial intelligence (AI) is rapidly changing the world around us. From the devices we use to the way we interact with businesses, AI is becoming an integral part of our lives. As AI continues to evolve, it's essential to have a basic understanding of how it works. One of the best ways to do this is to learn to code.
Coding is the language of computers. By learning to code, you'll gain a better understanding of how computers work and how they can be used to create AI applications. You'll also learn how to think algorithmically, which is a valuable skill for problem-solving in general.
👉How to get started Python: https://www.youtube.com/watch?v=EGdhnSEWKok
👉Beginner's Guide to Python Programming. Getting started now: https://youtu.be/ISv6XIl1hn0
👉Data Structures with Projects full tutorial for beginners
https://www.youtube.com/watch?v=lbdKQI8Jsok
👉OOP in Python - beginners Crash Course https://www.youtube.com/watch?v=I7z6i1QTdsw
Why You’re Struggling to Focus on Learning Coding Right Now
Ever feel like you want to learn coding, but something always gets in the way? It’s not just you. The biggest reason? Distractions and quick-fix alternatives.
Too many choices – So many languages, frameworks, and tutorials. Where do you even start?
No-code shortcuts – Tools promise app-building without coding, making it tempting to skip the fundamentals.
Overwhelming information – Everyone says, “Learn Python,” “No, learn JavaScript,” “No, AI is the future!”
The key? Pick one thing. Stick with it. Build real projects. Learning to code isn’t about keeping up with trends—it’s about creating something real.
👉How to get started Python: https://www.youtube.com/watch?v=EGdhnSEWKok
👉Beginner's Guide to Python Programming. Getting started now: https://youtu.be/ISv6XIl1hn0
👉Data Structures with Projects full tutorial for beginners
https://www.youtube.com/watch?v=lbdKQI8Jsok
👉OOP in Python - beginners https://www.youtube.com/watch?v=I7z6i1QTdsw
Ever feel like you want to learn coding, but something always gets in the way? It’s not just you. The biggest reason? Distractions and quick-fix alternatives.
Too many choices – So many languages, frameworks, and tutorials. Where do you even start?
No-code shortcuts – Tools promise app-building without coding, making it tempting to skip the fundamentals.
Overwhelming information – Everyone says, “Learn Python,” “No, learn JavaScript,” “No, AI is the future!”
The key? Pick one thing. Stick with it. Build real projects. Learning to code isn’t about keeping up with trends—it’s about creating something real.
👉How to get started Python: https://www.youtube.com/watch?v=EGdhnSEWKok
👉Beginner's Guide to Python Programming. Getting started now: https://youtu.be/ISv6XIl1hn0
👉Data Structures with Projects full tutorial for beginners
https://www.youtube.com/watch?v=lbdKQI8Jsok
👉OOP in Python - beginners https://www.youtube.com/watch?v=I7z6i1QTdsw
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How do you Get Started with Python (Without Getting Overwhelmed)
So, you’ve decided to learn Python—great choice! But where do you start? The internet is full of tutorials, courses, and advice, making it easy to feel lost. Here’s a simple roadmap:
🔥 Bonus: I’m offering free Python tutoring sessions for beginners—drop a comment if you’re interested! Let’s learn together. 🚀
Resources:
👉How to get started Python: https://www.youtube.com/watch?v=EGdhnSEWKok
👉Beginner's Guide to Python Programming. Getting started now: https://youtu.be/ISv6XIl1hn0
👉Data Structures with Projects full tutorial for beginners
https://www.youtube.com/watch?v=lbdKQI8Jsok
👉OOP in Python - beginners Crash Course https://www.youtube.com/watch?v=I7z6i1QTdsw
#Python #LearningToCode #CodingJourney #Beginners
So, you’ve decided to learn Python—great choice! But where do you start? The internet is full of tutorials, courses, and advice, making it easy to feel lost. Here’s a simple roadmap:
🔥 Bonus: I’m offering free Python tutoring sessions for beginners—drop a comment if you’re interested! Let’s learn together. 🚀
Resources:
👉How to get started Python: https://www.youtube.com/watch?v=EGdhnSEWKok
👉Beginner's Guide to Python Programming. Getting started now: https://youtu.be/ISv6XIl1hn0
👉Data Structures with Projects full tutorial for beginners
https://www.youtube.com/watch?v=lbdKQI8Jsok
👉OOP in Python - beginners Crash Course https://www.youtube.com/watch?v=I7z6i1QTdsw
#Python #LearningToCode #CodingJourney #Beginners
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Forwarded from Epython Lab
New to Linux? Learn the basic Linux commands for beginners in this easy-to-follow video tutorial. Master essential commands and start navigating your Linux system like a pro! https://youtu.be/yr65ibmN6-M
Don't forget to like, share, and subscribe for more data science and machine learning tutorials! If you have any questions or suggestions for future videos, please leave them in the comments below.
Don't forget to like, share, and subscribe for more data science and machine learning tutorials! If you have any questions or suggestions for future videos, please leave them in the comments below.
YouTube
Basic Linux Commands for Beginners
New to Linux? Learn the basic Linux commands for beginners in this easy-to-follow video tutorial. Master essential commands and start navigating your Linux system like a pro!
Don't forget to like, share, and subscribe for more data science and machine learning…
Don't forget to like, share, and subscribe for more data science and machine learning…
Why You Should Use Virtual Environments & Structure ML Projects Professionally 🚀
When working on machine learning projects, managing dependencies and maintaining a clean, scalable structure is crucial. Without proper organization, projects quickly become messy, unmanageable, and prone to conflicts.
🔹 Why Use Virtual Environments?
A virtual environment (venv) allows you to:
✅ Isolate dependencies for different projects. No more version conflicts!
✅ Ensure reproducibility—your project runs the same anywhere.
✅ Avoid system-wide installations that could break other Python applications.
How? https://youtu.be/qYYYgS-ou7Q
🔹 Why Structure ML Projects Properly?
A professional project structure helps with:
✅ Scalability—separate concerns (data, API, models, notebooks)
✅ Collaboration—team members can understand and contribute easily
✅ Automation—CI/CD for deployment and model updates
Typical ML Project Structure: https://youtu.be/qYYYgS-ou7Q
🔹 Why Use Git, GitHub, and CI/CD?
✅ Git & GitHub for version control & collaboration
✅ CI/CD (e.g., GitHub Actions) for automating testing & deployments
✅ Reproducibility & rollback—track and revert changes easily
💡 Pro Tip: Always maintain a README.md to document setup & usage instructions!
What challenges have you faced in structuring ML projects? Drop your thoughts below! 👇
#Python #MachineLearning #MLProject #GitHub #VirtualEnvironments #DataScience #CI_CD #SoftwareEngineering
When working on machine learning projects, managing dependencies and maintaining a clean, scalable structure is crucial. Without proper organization, projects quickly become messy, unmanageable, and prone to conflicts.
🔹 Why Use Virtual Environments?
A virtual environment (venv) allows you to:
✅ Isolate dependencies for different projects. No more version conflicts!
✅ Ensure reproducibility—your project runs the same anywhere.
✅ Avoid system-wide installations that could break other Python applications.
How? https://youtu.be/qYYYgS-ou7Q
🔹 Why Structure ML Projects Properly?
A professional project structure helps with:
✅ Scalability—separate concerns (data, API, models, notebooks)
✅ Collaboration—team members can understand and contribute easily
✅ Automation—CI/CD for deployment and model updates
Typical ML Project Structure: https://youtu.be/qYYYgS-ou7Q
🔹 Why Use Git, GitHub, and CI/CD?
✅ Git & GitHub for version control & collaboration
✅ CI/CD (e.g., GitHub Actions) for automating testing & deployments
✅ Reproducibility & rollback—track and revert changes easily
💡 Pro Tip: Always maintain a README.md to document setup & usage instructions!
What challenges have you faced in structuring ML projects? Drop your thoughts below! 👇
#Python #MachineLearning #MLProject #GitHub #VirtualEnvironments #DataScience #CI_CD #SoftwareEngineering
👍4
🚀 How to Become a Self-Taught AI Developer?
AI is transforming the world, and the best part? You don’t need a formal degree to break into the field! With the right roadmap and hands-on practice, anyone can become an AI developer. Here’s how you can do it:
1️⃣ Master the Fundamentals of Programming
Start with Python, as it’s the most popular language for AI. Learn data structures, algorithms, and object-oriented programming (OOP). Practice coding on LeetCode and HackerRank.
👉How to get started Python:https://youtube.com/playlist?list=PL0nX4ZoMtjYGSy-rn7-JKt0XMwKBpxyoE&si=N8rHxnIYnZvF-WBz
How to Create & Use Python Virtual Environments | ML Project Setup + GitHub Actions CI/CD https://youtu.be/qYYYgS-ou7Q
👉Beginner's Guide to Python Programming. Getting started now: https://youtube.com/playlist?list=PL0nX4ZoMtjYGSy-rn7-JKt0XMwKBpxyoE&si=N8rHxnIYnZvF-WBz
👉Data Structures with Projects full tutorial for beginners
https://www.youtube.com/watch?v=lbdKQI8Jsok
👉OOP in Python - beginners Crash Course https://www.youtube.com/watch?v=I7z6i1QTdsw
2️⃣ Build a Strong Math Foundation
AI relies on:
🔹 Linear Algebra – Matrices, vectors (used in deep learning) https://youtu.be/BNa2s6OtWls
🔹 Probability & Statistics – Bayesian reasoning, distributions https://youtube.com/playlist?list=PL0nX4ZoMtjYEl_1ONxAZHu65DPCQcsHmI&si=tAz0B3yoATAjE8Fx
🔹 Calculus – Derivatives, gradients (used in optimization)
📚 Learn from 3Blue1Brown, Khan Academy, or MIT OpenCourseWare.
3️⃣ Learn Machine Learning (ML)
Start with traditional ML before deep learning:
✔️ Supervised Learning – Linear regression, decision trees https://youtube.com/playlist?list=PL0nX4ZoMtjYGV8Ff_s2FtADIPfwlHst8B&si=buC-eP3AZkIjzI_N
✔️ Unsupervised Learning – Clustering, PCA
✔️ Reinforcement Learning – Q-learning, deep Q-networks
🔗 Best course? Andrew Ng’s ML Course on Coursera.
4️⃣ Dive into Deep Learning
Once comfortable with ML, explore:
⚡️ Neural Networks (ANNs, CNNs, RNNs, Transformers)
⚡️ TensorFlow & PyTorch (Industry-standard deep learning frameworks)
⚡️ Computer Vision & NLP
Try Fast.ai or the Deep Learning Specialization by Andrew Ng.
5️⃣ Build Real-World Projects
The best way to learn AI? DO AI. 🚀
💡 Train models with Kaggle datasets
💡 Build a chatbot, image classifier, or recommendation system
💡 Contribute to open-source AI projects
6️⃣ Stay Updated & Join the AI Community
AI evolves fast! Stay ahead by:
🔹 Following Google AI, OpenAI, DeepMind
🔹 Engaging in Reddit r/MachineLearning, LinkedIn AI discussions
🔹 Attending AI conferences like NeurIPS & ICML
7️⃣ Create a Portfolio & Apply for AI Roles
📌 Publish projects on GitHub
📌 Share insights on Medium/Towards Data Science
📌 Network on LinkedIn & Kaggle
No CS degree? No problem! AI is about curiosity, consistency, and hands-on experience. Start now, keep learning, and let’s build the future with AI. 🚀
Tagging AI learners & enthusiasts: What’s your AI learning journey like? Let’s connect!. 🔥👇
#AI #MachineLearning #DeepLearning #Python #ArtificialIntelligence #SelfTaught
AI is transforming the world, and the best part? You don’t need a formal degree to break into the field! With the right roadmap and hands-on practice, anyone can become an AI developer. Here’s how you can do it:
1️⃣ Master the Fundamentals of Programming
Start with Python, as it’s the most popular language for AI. Learn data structures, algorithms, and object-oriented programming (OOP). Practice coding on LeetCode and HackerRank.
👉How to get started Python:https://youtube.com/playlist?list=PL0nX4ZoMtjYGSy-rn7-JKt0XMwKBpxyoE&si=N8rHxnIYnZvF-WBz
How to Create & Use Python Virtual Environments | ML Project Setup + GitHub Actions CI/CD https://youtu.be/qYYYgS-ou7Q
👉Beginner's Guide to Python Programming. Getting started now: https://youtube.com/playlist?list=PL0nX4ZoMtjYGSy-rn7-JKt0XMwKBpxyoE&si=N8rHxnIYnZvF-WBz
👉Data Structures with Projects full tutorial for beginners
https://www.youtube.com/watch?v=lbdKQI8Jsok
👉OOP in Python - beginners Crash Course https://www.youtube.com/watch?v=I7z6i1QTdsw
2️⃣ Build a Strong Math Foundation
AI relies on:
🔹 Linear Algebra – Matrices, vectors (used in deep learning) https://youtu.be/BNa2s6OtWls
🔹 Probability & Statistics – Bayesian reasoning, distributions https://youtube.com/playlist?list=PL0nX4ZoMtjYEl_1ONxAZHu65DPCQcsHmI&si=tAz0B3yoATAjE8Fx
🔹 Calculus – Derivatives, gradients (used in optimization)
📚 Learn from 3Blue1Brown, Khan Academy, or MIT OpenCourseWare.
3️⃣ Learn Machine Learning (ML)
Start with traditional ML before deep learning:
✔️ Supervised Learning – Linear regression, decision trees https://youtube.com/playlist?list=PL0nX4ZoMtjYGV8Ff_s2FtADIPfwlHst8B&si=buC-eP3AZkIjzI_N
✔️ Unsupervised Learning – Clustering, PCA
✔️ Reinforcement Learning – Q-learning, deep Q-networks
🔗 Best course? Andrew Ng’s ML Course on Coursera.
4️⃣ Dive into Deep Learning
Once comfortable with ML, explore:
⚡️ Neural Networks (ANNs, CNNs, RNNs, Transformers)
⚡️ TensorFlow & PyTorch (Industry-standard deep learning frameworks)
⚡️ Computer Vision & NLP
Try Fast.ai or the Deep Learning Specialization by Andrew Ng.
5️⃣ Build Real-World Projects
The best way to learn AI? DO AI. 🚀
💡 Train models with Kaggle datasets
💡 Build a chatbot, image classifier, or recommendation system
💡 Contribute to open-source AI projects
6️⃣ Stay Updated & Join the AI Community
AI evolves fast! Stay ahead by:
🔹 Following Google AI, OpenAI, DeepMind
🔹 Engaging in Reddit r/MachineLearning, LinkedIn AI discussions
🔹 Attending AI conferences like NeurIPS & ICML
7️⃣ Create a Portfolio & Apply for AI Roles
📌 Publish projects on GitHub
📌 Share insights on Medium/Towards Data Science
📌 Network on LinkedIn & Kaggle
No CS degree? No problem! AI is about curiosity, consistency, and hands-on experience. Start now, keep learning, and let’s build the future with AI. 🚀
Tagging AI learners & enthusiasts: What’s your AI learning journey like? Let’s connect!. 🔥👇
#AI #MachineLearning #DeepLearning #Python #ArtificialIntelligence #SelfTaught
YouTube
How to Install Python & VSCode on Windows (Step-by-Step)
Want to start coding in Python on Windows? This beginner-friendly guide walks you through the setup process—from installing Python and VS Code to writing your first Python script. 🚀 Whether you're a beginner or switching to Python, this tutorial makes it…
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What Can You Do with Python?
If you’re just starting your coding journey or exploring new tools, you might wonder: What can I actually do with Python?
The answer? Almost anything in tech.
Resources to learn Python:
👉How to get started Python: https://www.youtube.com/watch?v=EGdhnSEWKok
How to Create & Use Python Virtual Environments | ML Project Setup + GitHub Actions CI/CD https://youtu.be/qYYYgS-ou7Q
👉Beginner's Guide to Python Programming. Getting started now: https://youtu.be/ISv6XIl1hn0
👉Data Structures with Projects full tutorial for beginners
https://www.youtube.com/watch?v=lbdKQI8Jsok
👉OOP in Python - beginners Crash Course https://www.youtube.com/watch?v=I7z6i1QTdsw
Want to join a free live Python tutoring session for beginners?
Comment "interested" and I’ll send you the details!
If you’re just starting your coding journey or exploring new tools, you might wonder: What can I actually do with Python?
The answer? Almost anything in tech.
Resources to learn Python:
👉How to get started Python: https://www.youtube.com/watch?v=EGdhnSEWKok
How to Create & Use Python Virtual Environments | ML Project Setup + GitHub Actions CI/CD https://youtu.be/qYYYgS-ou7Q
👉Beginner's Guide to Python Programming. Getting started now: https://youtu.be/ISv6XIl1hn0
👉Data Structures with Projects full tutorial for beginners
https://www.youtube.com/watch?v=lbdKQI8Jsok
👉OOP in Python - beginners Crash Course https://www.youtube.com/watch?v=I7z6i1QTdsw
Want to join a free live Python tutoring session for beginners?
Comment "interested" and I’ll send you the details!
👍2
The Bug That Taught Me More Than Any Tutorial
Last week, I ran into a bug that almost derailed a client demo.
A function that should have returned filtered results was quietly failing due to a simple logic oversight: an unintended mutable default argument in Python.
def get_filtered_data(filters=[]): # classic trap
...
Each call was modifying the default list, leading to unpredictable results. After debugging, I replaced it with:
def get_filtered_data(filters=None):
if filters is None:
filters = []
...
Takeaways:
Default mutable arguments in Python are a silent trap.
Writing tests isn't just a best practice—it’s your first line of defense.
Don’t just “write code that works”—write code that fails loudly and early when it breaks.
I’m sharing this because even experienced devs fall into these traps. The real lessons come from the messy, unpredictable parts of real-world coding.
Common mistakes of naming functions https://youtu.be/PY22gyHjLW8
Last week, I ran into a bug that almost derailed a client demo.
A function that should have returned filtered results was quietly failing due to a simple logic oversight: an unintended mutable default argument in Python.
def get_filtered_data(filters=[]): # classic trap
...
Each call was modifying the default list, leading to unpredictable results. After debugging, I replaced it with:
def get_filtered_data(filters=None):
if filters is None:
filters = []
...
Takeaways:
Default mutable arguments in Python are a silent trap.
Writing tests isn't just a best practice—it’s your first line of defense.
Don’t just “write code that works”—write code that fails loudly and early when it breaks.
I’m sharing this because even experienced devs fall into these traps. The real lessons come from the messy, unpredictable parts of real-world coding.
Common mistakes of naming functions https://youtu.be/PY22gyHjLW8