I hope you're enjoying Module 1 of the Handling Messy Supply Chain Data with Python tutorial!

Now, I bet you’re ready to unlock even more Python superpowers!

For just $17, you’ll unlock the second part of this tutorial, where we go beyond cleaning data and dive into business insights, powerful visualizations, and automated reporting—all without spending hours in Excel.

A step towards becoming a supply chain data-driven pro.

Upgrade now for just $17 and unlock the full tutorial (part 1&2) +Bonus-challenge! 👇👇👇

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Fix messy supply chain data with Python.

Unlock module 2 (more business insights, powerful visualizations, and automated reporting ...)

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Google colab notebook (code ready to run)

Bonus-challenge: US dataset (Google colab notebook)

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Here’s what you’ll learn:

📌 Answering key supply chain questions:

✅ What are the top-selling SKUs per year? ✅ Who are the best-selling wholesalers each year? ✅ Are there differences in sales between the December holidays and summer? ✅ What’s the average number of SKUs per order? ✅ What’s the average quantity per order?

📌 Visualizing your insights with Python:

📊 Bar charts – See top SKUs and best-selling wholesalers at a glance 📈 Seasonality analysis – Detect monthly sales patterns 🗺️ Geospatial sales maps – Instantly spot top-performing regions

📌 Automating reports so you never do the same work twice:

💡 Generate Excel reports in Python—no more manual updates ⏳ Save hours of work by automating insights

Examples

What you’ll get:

🎥 Step-by-step video lessons – Watch & follow along

💻 Full access to the code – Simply run it, no need to start from scratch

📂 Bonus US Dataset Challenge – A hands-on self-guided exercise with a new dataset

⏳ Lifetime access – Revisit the tutorial anytime, at your own pace

📌 PS:

Stick to the big picture, and don’t worry about every detail. Python mastery comes with time—but this is your first step toward transforming how you work with data.

This tutorial will NOT teach you Python from scratch. Learning Python takes time. Instead, this hands-on experience lets you see Python’s power in action—without getting lost in the code.

Let’s be honest… think about everything it takes to do this in Excel. 🤯