Digital Currencies and Business Models
Certificate Course - Financial Engineering - FE.1.3.I26
| Date | Nov 26-27, 2026 |
| Duration | 2 days |
| Location | On campus - Karlsruhe |
| Language | English |
| ECTS | Upon request |
| Cost | 1,550 € |
Fundamentals
Understand blockchain, trustless distributed systems, and digital currencies including cryptocurrencies, stablecoins, and CBDCs.
Technology
Analyze smart contracts, their logic, applications, and limits, as well as the architecture and risks of decentralized finance DeFi.
Applications
Evaluate blockchain-based business models such as asset tokenization and their economic impact on financial markets and commerce.
What you´ll explore
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Explore how digital currencies function, including cryptocurrencies, stablecoins, and central bank digital currencies, through the core roles of money.
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Understand blockchain technology, trustless distributed systems, and how they reshape financial markets and business models.
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Learn the principles of smart contracts, their applications, limitations, and real-world use cases.
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Analyze the architecture of decentralized finance (DeFi), including its opportunities, interoperability, and emerging risks.
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Examine blockchain-based business models such as asset tokenization, fundraising, and decentralized organizations.
Your key takeaways
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Understanding of blockchain technology and trustless distributed systems
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Ability to distinguish between cryptocurrencies, stablecoins, and CBDCs
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Knowledge of smart contracts, their applications, and limitations
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Insights into DeFi architecture, opportunities, and associated risks
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Evaluation of blockchain-based business models and economic implications
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Awareness of tokenization, decentralized organizations, and new financial structures
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Skills to assess the impact of digital currencies on financial markets and commerce
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Practical perspective on innovation using blockchain-based business concepts
Taught by Recognized Experts in Digital Currencies and Business Models
Benefit from the knowledge of leading specialists with extensive experience in research and industry. Their deep expertise guarantees a course of outstanding academic and practical quality.
Prof. Dr. Philipp Schuster
Prof. Dr. Philipp Schuster is Professor of Finance at the University of Stuttgart and a guest researcher at the Karlsruhe Institute of Technology (KIT). His work focuses on asset pricing, liquidity risk, and bond and derivatives markets. He previously held positions as postdoctoral researcher and junior research group leader at KIT, where he also completed his habilitation.
His research combines empirical analysis with financial modeling to better understand market frictions and financial innovation.
Who Should Attend
This module is designed for professionals seeking a structured introduction to machine learning and its applications in decision-making, finance, and advanced analytical modeling.
- Decision-makers and managers interested in understanding machine learning concepts and methods
- Finance professionals seeking data-driven approaches to market analysis and forecasting
- Analysts and researchers looking to strengthen their knowledge of applied and advanced machine learning techniques
- Professionals who want a coherent learning path from foundational to specialized topics
Advance your career with KIT-level expertise
Benefit from the reputation of the Karlsruhe Institute of Technology (KIT) while gaining practical skills, flexible learning opportunities, and a recognized certificate to support your long-term professional growth.
Flexibility
Gain focused expertise in a specific field without committing to a full degree program, allowing you to build relevant knowledge efficiently and integrate learning seamlessly into your professional routine.
Relevance
Benefit from high-quality academic content combined with practical insights, delivered by experienced experts, supporting continuous, lifelong learning while ensuring direct applicability in real-world scenarios.
Advancement
Enhance your professional profile with a recognized certificate, demonstrating your commitment to ongoing development and supporting your career with tangible, verifiable credentials.