Python Data Analysis with Developer Tools & AI (and #14DaysOfDataScience)
Tags: thisweekinai, beginners, datascience, ai
Published: 2024-03-16 14:35:29

---
title: Python Data Analysis with Developer Tools & AI (and #14DaysOfDataScience)
published: true
description: March 14 (PiDay) was also #PythonDataScienceDay and the mid-point of our #14DaysOfDataScience journey. In this post I share my roadmap for simplifying your data analysis journey with Developer Tools & AI - and kickstart a week-long tour of the developer tools I covered, one blog post at a time.
tags: thisweekinai, beginners, datascience, ai
cover_image: https://dev-to-uploads.s3.amazonaws.com/uploads/articles/jcij6o8rte1shk9xbq28.png
canonical_url: https://30daysof.github.io/data-science-day/week-2/
series: This Week In AI News
---

**Three Resources To Know This Week**

| Resource | Description |
|:---|:---|
| [Collection 1️⃣](https://aka.ms/2024-datasci-collection)|Skill up on Data Science Tools & Techniques |
| [Collection 2️⃣](https://aka.ms/rai-hub/collection)| Skill up on Responsible AI Principles & Tooling |
| [Collection 3️⃣](https://aka.ms/ai-studio/collection)| Build Generative AI Apps End-to-End with Azure AI|

Welcome to the tenth post in my [This Week In AI News](https://dev.to/nitya/series/25819) series. Want to keep up with my weekly posts? Now there's a tag you can follow: 👇🏽

{% tag thisweekinai %}

---

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**](https://techcommunity.microsoft.com/t5/ai-ai-platform-blog/a-code-first-experience-for-building-a-copilot-with-azure-ai/ba-p/4058659) 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](https://devblogs.microsoft.com/python/python-data-science-day/) - 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.

{% youtube scvDXfCMHYU%}

---

## 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](https://youtu.be/scvDXfCMHYU?t=3766) in the livestream.
 - Browse the talk slides here:

{% speakerdeck ece9c88c5e5242109b53dcac433b8f98 %}

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](https://aka.ms/workshops/python-data-analysis) 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**.

![Learning Roadmap](https://30daysof.github.io/data-science-day/_astro/DataScienceDay-Roadmap.ixBAXxDK_1SuePL.webp)

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](https://30daysof.github.io/data-science-day/) - 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.

![Data Science Lifecycle](https://media.dev.to/cdn-cgi/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2Fj4koxre4qs7azgv9i2k1.png)

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.

{% link https://dev.to/azure/welcome-to-14-days-of-data-science-lc9 %}

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

{% user paladique %}

{% user reneenoble %}

---

## 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.

![Make The Leap Into Data Science](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/wfpbr1yhujply69vflr1.png)

In the earlier section on Python Data Analysis (my Data Science Day talk), I shared a roadmap with a link to a [workshop repo](https://aka.ms/workshops/python-data-analysis) 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.

{% link https://dev.to/azure/data-science-devtools-github-codespaces-2fn %}

We will then build on that project throughout the week, to explore more tools and concepts, one post at a time. Check back for the updated list of posts here 👇🏽:

{% link https://dev.to/azure/data-science-devtools-visual-studio-code-jbg %}

---

## 5 | Self-Guided Learning Resources

Bookmark and revisit these for more information:

| Resource | Description |
|:---|:---|
| [Collection 1️⃣](https://aka.ms/2024-datasci-collection)|Skill up on Data Science Tools & Techniques |
| [Collection 2️⃣](https://aka.ms/rai-hub/collection)| Skill up on Responsible AI Principles & Tooling |
| [Collection 3️⃣](https://aka.ms/ai-studio/collection)| Build Generative AI Apps End-to-End with Azure AI|

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

{% tag thisweekinai %}

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

{% org azure %}