192.080 Crypto Asset Analytics
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2020S, VU, 2.0h, 3.0EC
TUWEL

Properties

  • Semester hours: 2.0
  • Credits: 3.0
  • Type: VU Lecture and Exercise

Learning outcomes

After successful completion of the course, students are able to

  • Explain distributed ledger technology and associated cryptoassets
  • Distinguish different types of cryptoassets by their function and technical characteristics
  • Apply fundamental analysis algorithms on cryptoasset transaction datasets
  • Implement specific cryptoasset analytics tasks with open source tools (BlockSci, GraphSense)
  • Explain features of privacy-centric cryptocurrencies and possible analysis approaches
  • Apply smart contract analytics tools
  • Analyze footprints of off-chain payment channels in blockchains
  • Present cryptoasset application use cases and scenarios
  • Design and implement their own cryptoasset analytics tasks

Subject of course

  • Cryptocurrencies and Distributed Ledger (Blockchain) Technology Recap
  • Fundamental Cryptocurrency Analytics Methods
  • Analysis of Privacy-Centric Cryptocurrencies (Monero, Zcash, etc.)
  • Analysis of Smart Contracts and Token Systems
  • Analysis of Off-Chain Payment and State Channels
  • Application Examples

Teaching methods

  • Lectures
  • Weekly homework assignments (Reading and programming tasks)
  • Presentations
  • Student project (specific data analytics task)

Mode of examination

Immanent

Additional information

This course features two 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.

Grading

  • Weekly Homework 50%
  • Student Project 50%

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Wed17:00 - 19:0004.03.2020 - 11.03.2020Seminarraum FAV 01 B (Seminarraum 187/2) Lecture
Crypto Asset Analytics - Single appointments
DayDateTimeLocationDescription
Wed04.03.202017:00 - 19:00Seminarraum FAV 01 B (Seminarraum 187/2) Lecture
Wed11.03.202017:00 - 19:00Seminarraum FAV 01 B (Seminarraum 187/2) Lecture

Examination modalities

ECTS Breakdown:
--------------------------------------------------

12h Lecture

13h Self-Study, Readings and Homeworks

50h Project

---------------------------------------------------
75h = (3 ECTS)

Course registration

Begin End Deregistration end
21.02.2020 10:00 09.03.2020 23:59 09.03.2020 23:59

Curricula

Literature

No lecture notes are available.

Previous knowledge

Prerequisites

  • Programming and analytics skills (e.g., Python, Scala, R).
  • Basic Knowledge of Bitcoin and Cryptocurrency Techniques (e.g., passing “VU 192.065 Cryptocurrencies”)
  • Basic knowledge of network analytics and machine learning techniques (clustering, classification)

Preceding courses

Language

English