“Data, data, data”

💻 [Async]

We kick off the course with an overview of what Data Science, as a discipline, is. There are two tasks for you to do ahead of class:

  • Watch the following introductory clip:

Slides

The slides used in the clip are available at:

Although not required, the clip mentions Lazer & Radford (2017) [lazer14032014] which, although not fully required for this course, is well worth your time if you are interested in new forms of data in the Social Sciences.

The paper, published under an Open Access license, is available here

  • Read “50 Years of Data Science”, by David Donoho [Don17].

Once you have read Donoho [Don17], the following table below will show you how the outline of this course can be mapped to his “Greater Data Science” goals:

Donoho’s Greater Data Science

  1. Data Gathering, Preparation, and Exploration

  2. Data Representation and Transformation

  3. Computing with Data

  4. Data Visualisation and Presentation

  5. Data Modeling

  6. Science about Data Science

Course Blocks

Goal

Computational building blocks

GDS3

Data Manipulation (Intro + Advanced)

GDS1 + GDS2

Exploring data visually

GDS4

Unsupervised learning

GDS5

[Supervised learning (Overview + Inference + Cross-Validation)

GDS5
Bibliography Computational building blocks