🗣️ Week 01 Lecture

Welcome to DS205 + Food Data Exploration

Author

Dr Jon Cardoso-Silva

Published

19 January 2026

Last Updated: 19 January 2026

Welcome to DS205, your gateway to professional-grade data engineering capabilities.

📍 Session Details

Date: Monday, 19 January 2026
Time: 16:00 - 18:00
Location: SAL.G.03

⚠️ IMPORTANT As this is still a relatively new course, we will be learning and adapting as we go. If you notice something that is not working super well or if you have any suggestions, please let me know!

📋 Preparation

Join our Slack workspace! Use this invitation link for the first time access
Go to the #social channel and show us some Slack interaction! Say hi and tell the group: why did you pick this course? feel free to also tell us: what is your degree programme? are you a former DS105 student? (that is, do you already know Jon?) if not, how did you learn Python?
Access DS205’s Nuvolos cloud platform. Follow the instructions in Nuvolos - First Time

🗣️ Lecture Structure

In our first DS205 lecture, we’ll cover the following:

Course Overview: Understand the core objectives and themes of DS205 and how we’ll progress from familiar food data to complex climate research. I will also discuss the structure and timing of our assessments. Those who joined this course from DS105 will find that it will be fairly similar.
Food Data Exploration Preview: We’ll explore the Open Food Facts API and see how systematic data inspection leads to sophisticated analysis. This demonstration shows the full pipeline from API collection to advanced clustering visualisation, giving you a preview of the analytical capabilities you’ll develop throughout the course.
Systematic Data Inspection: We’ll apply key pandas functions and systematic inspection methodology to real food product data. This serves as a brief recap of pandas and demonstrates transferable thinking patterns that work with any dataset.

🎬 Lecture Slides

Here you will find the slides used during the lecture.

Jon’s Slides

Use keyboard arrows to navigate. Select the slides below or view fullscreen.

Brief Practical Demonstration

During the final 30 minutes of the session, I covered:

VS Code environment setup
Open Food Facts API navigation and data collection
Systematic data inspection methodology
Jupyter Notebook demonstration: from API to clustering visualisation

Final Thoughts

Today’s lecture demonstrated the complete data pipeline: collecting data from APIs, applying systematic inspection patterns, engineering features, and using advanced techniques like UMAP clustering to reveal patterns in nutritional data. This preview shows where systematic thinking leads.

You’ll practice these foundational skills in Tuesday’s 💻 W01 Lab with Barry, and I will post solutions to the lab afterwards, too.

🎥 Session Recording

Typically, the recordings are made available on Moodle in the afternoon. I’ll update this section once the recording is available.

Jon 19 Jan 2026