💻 Week 02 - Class Roadmap (90 min)

2022/23 Lent Term

Welcome to the first seminar/lab class of DS101L.

Before we start covering the most technical aspects of data science, we want to take a step back and think about the bigger picture. That is why on 🧑‍🏫 Week 01 we asked you to do two things:

1. Collect data about yourself.
2. Read the indicative reading about the idea of the Quantified Self, and write your notes about it.

In this lab, we will discuss the readings and the data you collected and use them to reinforce the concept of tidy data, which you would have just seen in the 🧑‍🏫 W02 lecture, and discuss the best ways to exchange and share our reading notes.

Step 01 - Personal Data (20 min)

• Form groups of three
• Discuss your personal data:
  • What can you learn about yourself from this data?
  • Does it ‘paint a picture’ of you?
  • Would you be happy to share this data with anyone?
  • Which apps/companies do you think might have this type of data about you?
  • Do you think this is a good thing or a bad thing?
• Class teachers will facilitate a discussion with the wider group and share their expert opinion

Step 02 - Quantified Self, Identity, and Social Media (40 min)

• Form new groups of three
• Now, exchange the readings:
  • was there anything you did not understand?
  • was it all obvious, or was there anything interesting you had not thought about before?
  • how do the two readings connect?
  • do you agree with the conclusions of the authors?
• Discuss: how does the reading relate to the self-tracking exercise you did?
• Class teachers will facilitate a discussion with the wider group and share their expert opinion

Also:

• Discuss: how did you organise your notes? Can you, as a group, come up with best practices for note-taking?

Note

Later in this course, we will create a shared reading notes repository. For now, keep using your favourite note-taking app and share your notes with your group.

Step 03 - Tidy Data (30 min)

• Create a spreadsheet with your data (use MS Excel, Excel Online, Google Sheets, or LibreOffice Calc)
• Make it “tidy” (see 🧑‍🏫 W02 lecture for details)
• Ask class teachers to check your work