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.
[フレーム]
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
Related Articles
Take Microsoft's Python Web Apps Course For Free
To be informed about new articles on I Programmer, sign up for our weekly newsletter, subscribe to the RSS feed and follow us on Twitter, Facebook or Linkedin.
Scrimba's Backend Developer Path
25/11/2025
Scrimba has added a Backend Developer Path, focused on the JavaScript ecosystem, to its catalog. It is very project-focused, which is perfect for building a portfolio. It is one of Scrimba's [ ... ]
Europe Gets Its Own LLM
10/11/2025
EuroLLM is a fully open-sourced large language model made in Europe and built to support all twenty-four official EU languages.
- AI Champion Ship Now Open
- Kotlin 2.3 Improves Swift Interop
- What Does JetBrains Survey Tell Us About AI
- Move Fast And Fix Things - In Praise Of Rust
- InfluxDB 3.6 Released With AI Capabilities
- Epic Settles With Google - Abandons The Rest Of Us
- W3C Adopts A New Logo
- .NET 10, C# 14 and F# 10 Released Alongside Visual Studio 2026
- Codacy Provides Free AI- Risk Assessment
- Vibe Coding Is Collins Word of the Year 2025
- Apache Grails 7.0 Released
- State of the Octoverse 2025
- Vaadin Now Does MCP
Comments
or email your comment to: comments@i-programmer.info