LSE DS202 – Data Science for Social Scientists

2024/25 Winter Term

Author

Dr. Ghita Berrada

Important

The TQARO survey for this course is now live!🗳️ Take a moment and fill it in here. It’s really important to us! Thank you!

P.S: In the survey, teacher does not only mean class teacher but everyone you’ve interacted with (e.g your lecturer).

📑 Notice Board

🥐 Releases for this week:

Lab solutions

Formatives

  • You could take a look at this W07 formative model solution
  • Your personalised W07 formative feedback is available as an issue on the GitHub repository where you submitted your formative (the feedback will be replicated on Moodle eventually).

Summatives

Tutorials and lectures

  • Check out a quick tutorial on scikit-learn’s Pipelines (this is a handy feature when you want to chain multiple pre-processing and modeling steps together!)

  • The W07, W08 and W09 notebooks have been updated:

    • there were some small updates to references/links at the very end of the PCA section in the W07 notebook
    • in the W08 notebook, the code for Part 4: What if I have way more than two dimensions? has been corrected and a small note was added at the end of the part to discuss the fact that label-encoded categorical features dominate the principal components.
    • the missing explanations about the Gower metric were in the W09 notebook (and the change was mirrored in the W08 notebook where the Gower metric part originally appeared!). The code for the UMAP-generated plot after DSBSCAN with Gower was also fixed: label-encoding was wrong and producing unintended results so it was replaced with one-hot encoding

  • links to LOF videos in the W09 notebook were added to the W09 notebook

  • The W10 notebook has been updated:

    • some alternative code for how to generate a DFM with n-grams has been added to section 1.2 The notion of a Document-Term Feature Matrix
    • some visualisation of LDA topics has been added to section 2.3 Topic modelling
    • a section 2.4 Keyness analysis has been added on keyness analysis
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🧑🏻‍🏫 Our Team

Photo of Dr Ghita Berrada
Dr. Ghita Berrada
Assistant Professor of Data Science (Education)
LSE Data Science Institute
📧
COURSE CONVENOR LECTURER
Photo of Tabtim Duenger
Tabtim Duenger
Data Scientist at The Economist
MSc in Applied Social Data Science (LSE)
📧
CLASS TEACHER
Photo of Andreas Stöffelbauer
Andreas Stöffelbauer
Data Scientist at Microsoft
MSc in Data Science (LSE)
📧
CLASS TEACHER
Photo of Stuart Bramwell
Dr Stuart Bramwell
Guest Lecturer at the Data Science Institute
DPhil in Politics (Oxford University)
📧
CLASS TEACHER
Photo of Yassine Lahna
Yassine Lahna
Data Scientist
MSc in Statistical Science (Oxford University)
📧
CLASS TEACHER
Photo of Sara Luxmoore (with a cat!)
Sara Luxmoore
Research Officer
LSE Data Science Institute and LSE Cities
📧
SUPPORT SESSIONS

Could this be you?

Course reps are the link between the students and the academic staff. They attend Teaching Committee meetings to share students’ feedback and suggestions. As a perk, course reps are guaranteed a place in the industry trips we organise.

Learn how to nominate yourself on the 🗳️ Course Rep page.

Photo of Kevin Kittoe
Kevin Kittoe
Teaching and Learning Administrator
LSE Data Science Institute
📧
ADMIN

📍 Lecture

  • 📆 Fridays*
  • ⌚ 14:00 - 16:00
  • 📍 CKK.LG.09 (🗺️ campus map)
  • Lecturer:
    • 👩🏻‍🏫 Ghita

* except Week 06 - Reading Week

💻 Class Groups

Group 01

  • 📆 Mondays
  • ⌚ 09:00 - 10:30
  • 📍 FAW.3.04
  • 🧑‍🏫 Andreas*

* except Week 01 (Tabtim)

Group 02

  • 📆 Mondays
  • ⌚ 13:00 - 14:30
  • 📍 FAW.3.04
  • 🧑‍🏫 Stuart


Group 03

  • 📆 Mondays
  • ⌚ 15:00 - 16:30
  • 📍 FAW.3.04
  • 🧑‍🏫 Tabtim

* except Week 01 (Andreas)

Group 04

  • 📆 Mondays
  • ⌚ 16:30 - 18:00
  • 📍 FAW.3.04
  • 🧑‍🏫 Yassine


🛟 Additional weekly support sessions

Every week, we will offer drop-in sessions (no booking required) where you can get help with the week’s homework or with an upcoming assessment, ask questions about the lectures and classes, or simply chat with your peers and teachers.

  • 📆 Wednesdays
  • ⌚ 10.00-11.30
  • 📍 COL.1.06 (Visualisation Studio)
  • 🧑‍🏫 Sara