Simplifying Data Analysis & Visualization with Developer Tools & AI | Python Data Science Day

Having data analysis and visualization skills is increasingly important in the new age of Large Language Models and generative AI. But how does a non-Python developer skill up rapidly with the tools & best practices required to achieve project goals, without having the benefit of years of Python or data science experience? This is where the right developer tooling, with a little bit of AI assistance, can help. In this talk, we'll go from identifying an open-source data set, to analyzing it for insights and visualizing relevant outcomes, in 25 minutes - with just a GitHub account and an OpenAI endpoint. Along the way, we'll introduce you to a series of developer tools that make your journey easier: - Open Dataset: to ""analyze"" - from Kaggle, Hugging Face, or Azure - Data Wrangler: to ""sanitize"" data - extension from Visual Studio Code - Jupyter Notebook: to ""record"" process - for transferable learning - GitHub Codespaces: to ""pre-build"" environment - for consistent reuse - GitHub Copilot: to ""explain/fix"" code - for focused learning with AI help - Microsoft LIDA: to ""suggest/build"" visualization goals - for building your intuition with AI help The talk comes with an associated repo that you can fork - then replace with your own dataset to extend or experiment on your own later. By the end of the talk you should have a sense of how you can go from discovering a data set to getting some visual insights about it, using existing tools with a little AI assistance. Chapters: 00:00 Simplifying Data Analysis & Visualization with Developer Tools & AI 00:29 Follow along 00:54 Introduction - Data Analysis Challenges & Goals 04:44 GitHub Codespaces - Reusable environments 08:32 Jupyter Notebooks - Make it reproducible 11:18 GitHub Copilot - AI-assisted learning 14:43 Visual Studio Code - Productivity extensions 15:39 Open Datasets - Data Wrangler 19:15 Resonsible AI toolkit - Model debugging for fairness 21:13 Project LIDA - AI-assisted intuition & visualization 25:24 Azure AI Studio - Paradigm shift to LLM Ops 25:47 Summary - Questions & Next Steps   Resources: 30 Days of Data Science: https://30daysof.github.io/data-science-day/week-2/ Data Science Recipes: https://aka.ms/2024/data-science-recipes Workshops: https://aka.ms/workshops/python-data-analysis Survey https://aka.ms/Python/DataScienceDay/Survey Python at Microsoft https://aka.ms/python Cloud Skills Challenge - through April 15, 2024 https://aka.ms/Python/DataScienceDay/CSC GitHub codespaces https://github.com/codespaces VS Code Release notes https://code.visualstudio.com/updates Featuring: Nitya Narasimhan, PhD, Senior AI Advocate, Microsoft (@nitya) 📲 Follow VS Code: * X: https://x.com/code * Bluesky: https://bsky.app/profile/vscode.dev * LinkedIn: https://aka.ms/VSCode/LinkedIn * GitHub: https://github.com/microsoft/vscode