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.

2022S, VU, 2.0h, 3.0EC

Properties

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

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
  • 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

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

Teaching methods

  • Lectures
  • Weekly homework assignments (Paper 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, invited talks, and weekly homework assignments, mostly 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 - 18:3009.03.2022 Zoom Meeting (LIVE)Course Intro & Cryptoasset Recap
Wed17:00 - 18:3016.03.2022 Zoom Meeting (LIVE)Basic Cryptoasset Analysis Techniques
Wed17:00 - 18:3023.03.2022 Zoom Meeting (LIVE)The Limits of Known Methods: Coin Mixing & Privacy Coins
Wed17:00 - 18:3030.03.2022 Zoom Meeting (LIVE)Going Beyond UTXO: Ethereum, Smart Contracts, Tokens, Account-Model Ledgers
Wed17:00 - 18:3020.04.2022 Zoom Meeting (LIVE)Analyzing Decentralized Finance (DeFi) Protocols
Wed17:00 - 18:3027.04.2022 Zoom Meeting (LIVE)Analyzing Layer-2 (Lightning Protocol) + Machine Learning Techniques
Wed17:00 - 18:3004.05.2022 Zoom Meeting (LIVE)Projects | Overall Approach & Initial Design Presentation
Wed17:00 - 18:3001.06.2022 Zoom Meeting (LIVE)Projects | Intermediate Results Presentation
Wed17:00 - 19:0029.06.2022EI 1 Petritsch HS Projects | Final Results Presentation

Examination modalities

ECTS Breakdown:
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12h Lecture

13h Self-Study, Readings and Homeworks

50h Project

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75h = (3 ECTS)

Course registration

Begin End Deregistration end
18.02.2022 10:00 28.02.2022 23:59 09.03.2022 23:59

Curricula

Study CodeSemesterPrecon.Info
066 645 Data Science
066 645 Data Science STEOP
Course requires the completion of the introductory and orientation phase
066 937 Software Engineering & Internet Computing
175 FW Elective Courses - Economics and Computer Science
880 FW Elective Courses - Computer Science

Literature

No lecture notes are available.

Previous knowledge

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

Preceding courses

Language

English