Python Data Analysis with Developer Tools & AI (and #14DaysOfDataScience)

Three Resources To Know This Week

Welcome to the tenth post in my This Week In AI News series. Want to keep up with my weekly posts? Now there’s a tag you can follow:

In my previous posts, I’ve talked about LLM Ops and the application lifecyle for building generative Read my tech community post on the topic for a quick refresher and core sample repos. Then, let’s shift left even further, and think about where it all starts — with data science and analysis. Here’s what we cover in this post:

• 1 | Python Data Science Day
• 2 | Python Data Analysis Workshop
• 3 | Week 1 – A Focus on Fundamentals
• 4 | Week 2 – A Focus on Developer Tools
• 5 | Self-Guided Learning Resources

1 | Python Data Science Day

March 14, 2024 (3.14) was Pi Day aka Python Data Science Day at Microsoft – a full-day of talks from Python enthusiasts and experts from all over the world. Watch the replay of the 8-hour livestream below, and check the description for the complete list of talks with timestamped links into the stream for quick access.

2 | Python Data Analysis Workshop

I presented a talk on Simplifying Data Analysis with Developer Tools & AI targeting the non-Python developer. My target audience was someone new to Python or Data Science, but otherwise experienced in development. And my goal was to provide a learning roadmap and quickstart environment so they could get productive quickly in their data science journey.

• Find the talk video at this timestamp in the livestream.
• Browse the talk slides here:

In that talk, I outlined the following roadmap for developers new to this topic, to structure their learning journey but also create a reusable, shareable and reproducible development environment for producitivity. And I share a workshop repo I am maintaining, that can take developers from conceptual understanding to hands-on practice. Want to learn more? Check out the Week 2 section below.

But wait – what if you wanted to have a more structured roadmap of what to learn, and where to look for resources to learn it? We have you covered! Say hello to #14DaysOfDataScience – a series that bookends the Data Science Day event with 2 weeks of daily blog posts focused on Data Science & Developer tools authored by Data & AI Advocates at Microsoft.

3 | Week 1 – A Focus on Fundamentals

The first week of the series focused on Data Science Foundations – from the definition of data science, to understanding the data science application lifecycle end-to-end. Along the way, you’ll also get an introduction to machine learning (supervised and unsupervised) and responsible AI, and understand what the data science developer experience involves.

Check out the series today, starting with this first post which also contains a series listing that makes it easy to find the other posts, including upcoming ones in Week 2.

Want to learn more about data science fundamentals? Follow these Week 1 authors right here on dev.to:

4 | Week 2 – A Focus on Developer Tools

The second week of the series focuses on Developer Tools taking you from concepts (week 1) to code (week 2) with hands-on exercises to solidify what you learn.

In the earlier section on Python Data Analysis (my Data Science Day talk), I shared a roadmap with a link to a workshop repo that will be a source for these hands-on exercises. This week, I will be updating that repo and publishing one post each day, to showcase *one developer tool at a time.

The series kicked off yesterday with this post that helps set the stage with a look at Dev Containers & GitHub Codespaces. By the end of this post, you should have forked the repo and validated that you have a working development environment with Jupyter Notebook support – that we can build on throughout the week, to explore more tools and concepts.

And stay tuned for the next post where we’ll talk about how you can create a reusable profile for Visual Studio Code, and complete your first data science tutorial using this environment.

5 | Self-Guided Learning Resources

Bookmark and revisit these for more information:

And don’t forget to follow this tag for updates from This Week in AI News:

And follow our Azure publication right here on dev.to for more articles from the Cloud Advocacy and Product Teams at Microsoft: