Syllabus

Instructors

Dirk Wulff (contact), Rui Mata (contact)

Venue

CDS meeting room, Missionstrasse 64A, 1^st floor

Background

Data is everywhere and is being used to answer many questions concerning our wealth, health, and productivity. The aim of this seminar is to enable you to thoughtfully and actively use data science to help answer meaningful questions in a wide variety of domains. The course will consist of 1) introductory sessions on data science techniques using R, 2) the application of these techniques in a group project over the course of the semester, 3) discussion with experts (meet-the-expert events) to learn about opportunities and challenges of data analytics in psychology and business.

Goals

Learn the fundamentals of data science, develop confidence and skills in wrangling, analyzing, and communicating data to answer questions in an evidence-based manner.

Grading

The course is graded as PASS/FAIL. Students can receive a PASS if they fulfill the following requirements:

1. Engagement in class exercises and discussions including meet-the expert events
2. Complete homework assignments
3. Present a blitz talk describing the group project (cf. session 2)
4. Contribute to and complete group project
5. Present group project (cf. session 4)

Agenda

The course consists of 4 sessions on the following Fridays (ca. 9:00 to 16:00)

Session	Date	Contents
1	21.02.2020	Introduction to data science; exploratory data analysis; project selection
2	17.04.2020	Statistical modeling and causal inference; machine learning; student blitz talks
3	24.04.2020	Project meetings
4	15.05.2020	Student presentations; meet-the-expert event

Course Readings

Course readings will be provided throughout the semester.