Cryptocurrencies such as Bitcoin, Initial Coin Offerings (ICOs), and Distributed Autonomous Organizations (DAOs) are well-known crypto asset examples. They build on blockchain technology and form virtual ecosystems in which different actors interact with each other with varying intentions. The general availability of transaction data in the underlying blockchains led to the development of a number of analytics techniques that are nowadays used for reasons such as market research, compliance and anti-money-laundering, as well as law enforcement.

The goal of this course is to learn how crypto asset ecosystems can be analyzed using a variety of data science methods and how gained insights can subsequently be used for informed decision making. The course will offer the opportunity to design and develop novel approaches for a number of analytics use cases.

• Introduction to Crypto Currencies, and Crypto Assets

• Distributed Ledger Technology (Blockchain)

• Distributed Computing Platforms and Token Systems

• Graph and Network Analysis Fundamentals

• Analyzing Cryptocurrencies: Network Abstractions & Heuristics

• Crypto Asset Analytics Tools

• Analyzing von Smart Contracts & Token Systems

• Application Examples & Recent Developments

Pedagogic Concept

This course features two subsequent parts: the first part (beginning of the semester) will feature lectures held by the instructor and weekly homework assignments encompassing programming / analytics tasks or examination and in-class presentation of related work and literature. In the second part, students will build on learned analytics methods and techniques and work on a defined project in the field of crypto asset analytics.

• Weekly Homework 30%

• Student Project 40%

• Written Exam 30%

• Programming skills (e.g., Python, Scala, R).

• Basic Knowledge of Bitcoin and Cryptocurrency Techniques