Welcome to CSS 2!#

CSS 2 | Sean Trott | Winter 2024 | UCSD

Course Overview#

This course will teach how you to think about data and modeling for computational social science.

  • How is a dataset formatted, and is this the appropriate format for what I want to do?

  • Is this dataset representative or does it reflect a biased sample?

  • What ethical considerations should I take into account when obtaining and analyzing data?

  • What kind of model is the most appropriate for these data?

  • How do I design and implement these models––ranging in complexity from linear regression to support vector machines?

This course is one of the three core courses for the CSS Minor at UCSD, along with CSS 1 and CSS 100. Note that CSS 1 is a prerequisite for this course; please see the course expectations page for more information.

Grading#

Your grade will be determined by your performance on weekly labs, several problem sets, and a final project.

There are no midterms or final exams; see the syllabus for more details.

Current Iteration#

The current iteration of CSS 2 is Winter 2024. The instructor is Sean Trott.

Topics#

Topics covered will include:

  • Ethical issues: bias, fairness, privacy, and more.

  • Data visualization.

  • Linear models.

  • Classification.

  • Unsupervised approaches.

For more details, check out the syllabus.