Decentralized Finance

Understanding the future of financial infrastructure through hands-on exploration of DeFi protocols, smart contracts, and blockchain technology.

Start Learning View Syllabus
12
Weeks
13
Lessons
45
Terms
6
Credits

Course Modules

Module 1: Foundations

Weeks 1-3
  • DeFi ecosystem overview
  • Blockchain and smart contracts
  • Token standards and economics
Progress 3/3 weeks
Completed

Module 2: Core Protocols

Weeks 4-6
  • Automated Market Makers
  • Lending and borrowing
  • Stablecoin mechanisms
Progress 3/3 weeks
Completed

Module 3: Strategies

Weeks 7-9
  • Yield farming and liquidity mining
  • Derivatives and synthetics
  • Oracle mechanisms
Progress 1/3 weeks
In Progress

Module 4: Advanced Topics

Weeks 10-12
  • Governance and DAOs
  • Security and MEV
  • Scaling and cross-chain
Progress 0/3 weeks
Upcoming

Slides

All lecture presentations

Quizzes

Weekly self-assessments

Exercises

Hands-on assignments

Glossary

Key DeFi terminology

Getting Started

Setup instructions

GitHub

Source repository

Weekly Schedule

Week Topic Materials
1 Introduction to DeFi Exploring DeFi Data
2 Blockchain Foundations Interacting with Smart Contracts
3 Tokens and Standards Token Analysis
4 Decentralized Exchanges AMM Mechanics
5 Lending Protocols Lending Protocol Analysis
6 Stablecoins Stablecoin Analysis
7 Yield Farming and Liquidity Mining Yield Farming Simulation
8 Derivatives and Synthetics Derivatives Analysis
9 Oracles and Data Feeds Oracle Analysis
10 Governance and DAOs Governance Analysis
11 Security and Risk Security Analysis
12 Future of DeFi L2 Analysis
13 DeFi_Regulation  

Prerequisites

Before You Begin This course assumes familiarity with the following areas. Don't worry if you're not an expert - we'll build on these foundations together.

Programming

  • Python 3.10+ proficiency
  • pandas, numpy experience
  • Data visualization skills

Blockchain

  • Transaction concepts
  • Consensus mechanisms
  • Wallet basics

Finance

  • Time value of money
  • Risk/return tradeoffs
  • Basic derivatives

Statistics

  • Probability distributions
  • Hypothesis testing
  • Regression analysis

Learning Path

Recommended Approach Follow this structured approach for each week to maximize your learning: 1. **Review** - Study slides and lecture materials 2. **Practice** - Complete Jupyter notebook exercises 3. **Test** - Take the weekly self-assessment quiz 4. **Apply** - Work through weekly assignments 5. **Discuss** - Engage with the course community

Course Information

Instructor
Prof. Dr. Joerg Osterrieder
Institution
FHGR - University of Applied Sciences of the Grisons
Semester
Spring 2025
Credits
6 ECTS

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© 2025 Prof. Dr. Joerg Osterrieder | FHGR - University of Applied Sciences of the Grisons