StudyLab 1. semester KDS (Autumn 2023)

Advanced Applied Statistics (Autumn 2023)

Advanced Network Science (Autumn 2023)

The following is the list of chapters from the textbook you're expected to study.

The textbook is "The Atlas for the Aspiring Network Scientist" (https://www.networkatlas.eu/)

  • L2: Node Classification (Chapter 12)
  • L3: Deep Learning on Graphs (Chapter 37)
  • L4: Graph Summarization (Chapter 38)
  • L5: Frequent Pattern Mining (Chapter 39)
  • L6: Network Distances (Chapters 40-41)
  • L7: High Order Dynamics (Chapter 30)
The papers to read are:

  • L8: Watts & Strogatz. Collective dynamics of ‘small-world’ networks
  • L9: Albert et al. Error and attack tolerance of complex networks
  • L10: Watts. A simple model of global cascades on random networks
  • L11: Girvan & Newman. Community structure in social and biological networks
  • L12: Christakis & Fowler. The spread of obesity in a large social network over 32 years
  • L13: Cha et al. Measuring user influence in twitter: The million follower fallacy
  • L14: Grover & Leskovec. node2vec: Scalable feature learning for networks

Advanced Natural Language Processing and Deep Learning (Autumn 2023)

Seminars in Data Science (Autumn 2023)

Data in the Wild: Wrangling and Visualising Data (Autumn 2023)