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Humboldt-Universität zu Berlin - Statistics

Blockchain and cryptocurrency seminar


Course 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. 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 . Direct computer oriented knowledge and possibilities of empirical research will be shown. The course is televised to NUS, Singapore. Together with the Dept STAT of NUS we present extremely practical examples from finance, neuro economics and network analysis.


The lectures take place Tuesdays from 9:00-12:00, Dorotheenstr. 1, Room 005; if not otherwise stated.



- iCloud Account

- Working Laptop (MacBooks prefered)


Course Learning Objectives

- Understand the Blockchain Economy

- Learn essential programming languages such as Python

- create your own content in regards to Blockchain Applications, see shared numbers file: https://www.icloud.com/numbers/BCS_SS19


Course Structure

Every participant of the course has to work on a project in order to complete the course. Possible projects might be discussed in advance with the course supervisors in order to check for feasibility. Therefore, each participant has to think of a project he would like to work on. Please bring your Laptop (MacBooks prefered) to the event.


Literature to inspire your project:


Visualization Techniques: http://statweb.stanford.edu/~tibs/sta306bfiles/xgvis.pdf

 Regularisation and Model Selection: http://www2.stat.duke.edu/~rcs46/lectures_2015/08-reg2/03Models_v2.pdf

Bagging and Bootstrap of CARTs: http://www.stat.cmu.edu/~ryantibs/datamining/lectures/24-bag.pdf

Network and Fraud Detection :https://www.sas.com/content/dam/SAS/en_be/doc/other2/sas-forum-belux-2014/KULeuven-SAS-Analytics-Presentation.pdf

Develop  CRRIX = Crypto Regulatory IndeX from: https://cointelegraph.com


Feel free to search through Quantlet.de for further inspiration



Literature and Sources

 qlet.pngwww.quantlet.de (source codes)