Description:
The evolution from analogue to digital technologies continues to dominate the attention of decision makers today. Many tools in industrial production processes have been automated or replaced by highly complex mechanisms with pre-programmed decision-making. The change to digital modes of operations increasingly determines the lives of individuals and does so in increasingly unexpected ways.
The students get insight into the area of modern internet based Computational Statistics Methods and Time Series Analysis in Python. Practically relevant knowledge on methods, data forms and Gestalt will be trained. The use of GITHUB and network techniques will be taught and transferred into www.quantlet.de and www.quantinar.com. Direct computer oriented knowledge and possibilites of empirical research will be shown.
Detailed information about project: During the course of the lecture, students work a project. The research question is either self-proposed by the students or given by the lecturer. The project must contain a data analysis in Python. Ongoing project updates should constantly be presented in the lecture. The code has to be transparently available and reproducible on Quantlet.
Time & venue:
Mondays, 16:00-20:00; HU Berlin, Spandauer Str. 1, room 22
Exam:
Portfolio exam: The course is completed with a project and an oral exam (20 min). The projects are presented in the last lecture and the oral exam is in the following week.
More information can be found on Moodle.
