Computational Thinking with Jupyter & Causal Inference 🚀
Dettagli
Ciao Pythonistas! 🐍
Get ready for our next PyData Milano gathering! We are back this January featuring two incredible talks that bridge the gap between learning to code and applying advanced data science in the real world.
Join us for an evening of learning, networking.
🗓️ When: Wednesday, January 28th 📍 Where: TeamSystem
🎤 Talk 1: Learn Python with Jupyter By Serena Bonaretti (Independent Teacher & Researcher)
Are you tired of programming books that just teach syntax? Serena introduces a new approach. Instead of treating Python like a grammar book, her method uses Jupyter Notebooks to build Computational Thinking. We will explore how to move from concrete concepts to abstract reasoning, using narrative-driven code to truly master the language. 🔗 Check out her material: www.learnpythonwithjupyter.com
🎤 Talk 2: From Correlation to Causation By Andrea Mosca (Senior Data Scientist @ Data Reply)
Predictive models are great, but they don't always tell you why something happens. Andrea will guide us through the world of Causal Inference, moving beyond standard machine learning.
- The Theory: Why correlation is not enough for decision-making.
- The Practice: Real-world applications like Price Elasticity and Uplift Models for marketing.
- The Goal: Unlocking better decisions through cause-effect relationships.
🙏 Sponsors A big thank you to NumFOCUS for supporting our community!
RSVP now to save your spot. See you there! 👋
⚠️ Is necessary to provide your actual name and surname and a valid email to receive the QR code to access the venue, no exceptions.
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