aka Dan Kornas who runs a very successful X account about everything related to engineering ML applications. And what is he using in his tutorials? Python, of course.

By launching the Programming Python Fundamentals video tutorial he aims to get beginners starting with Python in order to set the absolute minimum requirement for getting into AI. In fact this is very first step on his AI Learning Roadmap :

• Programming: Covering Python and other programming languages relevant to AI.
  
  
• Working with Data: Introducing tools like Pandas, NumPy, and data visualization libraries.
  
  
• Machine Learning: Teaching core algorithms, evaluation metrics, and tuning techniques.
  
  
• Deep Learning: Exploring neural networks, advanced architectures, and applications.
  
  
• MLOps and Model Deployment: Bridging the gap between experimentation and production.

Dan in the very near future is going to launch a complete ML engineering bootcamp accessible as the "Open Source AI Learning Hub". The site is up already but the tutorials are not there yet. To get notified upon its launch make sure to sign up for Dan's newsletter.

Until that time comes we can prepare ourselves by going through his Python fundamentals mini course, packed as
a 14 part youtube list. The code walkthroughs are based on the Google Colab platform, run as Jupyter notebooks.
As such the very first lesson is on Colab's functionality and how to use it to run code following along.

Then we're jumping straight on to the bare bone fundamentals in "Comments & Printing". Well the title is not much representative of the actual material since it also includes variables and well yes, how to print their values.

Variables are further explored among with dynamic typing and Python's data types in "Data Types & Variables".
The next lesson is all about Strings - how to create strings using single, double, and triple quotes, understanding escape sequences, concatenating strings, slicing etc

The next four lessons are about data types closely related : Lists, Tuples, Sets and Dictionaries; necessary to understand for any kind of data science work.

Next off are Conditionals, Loops, Functions, Handling files, exceptions and finally Classes.

All the 14 videos in the playlist range from 5 to 25 minutes, so they're quick to follow. They're also easy follow because of Dan's quality presentation and conveyance of the concepts at hand.

To conclude, this is a quality resource to get you started with programming in Python and set the foundations for the further exploration of machine learning and data science.

More Information

Programming Python Fundamentals on Youtube

Open Source AI Learning Hub 

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