Module: Engineering Aspects of Financial Markets
This certificate module combines two complementary short courses in a structured learning path.
Participants gain a broad understanding of financial engineering, covering core principles of financial markets, fundamental engineering methods, and derivatives with the valuation of optionality.
General Information
| Dates | Jun 12 - 23, 2027 |
| Duration | 10 days |
| Location | On campus - Karlsruhe |
| Language | English |
| ECTS | 8 |
| Cost | 4,980 € |
Further questions?
Martina Waldner
Senior Program Consultant
info∂hectorschool.kit.edu
+49 721 608 47880
Program Structure
The full certificate module consists of two interconnected short courses. While each course can be attended individually, the complete module offers a coherent learning journey from foundational concepts to advanced machine learning applications
Fundamentals of Financial Engineering
Deterministic and stochastic methods for financial engineering; market modeling, derivatives, and valuation principles
| Date | Jul 12 - 13 and 19 - 20, 2027 |
| Duration | 4 days (Mo. to Tue. and Mo. to Tue. next week) |
Derivatives and Value of Optionality
Derivatives and optionality valuation; option pricing, hedging strategies, and timing considerations
| Date | Jul 14 - 16 and 21 - 23, 2027 |
| Duration | 6 days (Wed. to Fr. and Wed. to Fr. next week) |
How the Courses Fit Together
Participants first build a foundation in financial engineering principles and market instruments, then develop an understanding of derivatives, optionality, and pricing and hedging methods, and finally deepen their knowledge of timing effects in financial decision-making and advanced valuation concepts.
Who should attend
This module is designed for professionals seeking a structured introduction to AI-driven service innovation and business transformation, with a focus on digital services, service design, and applied AI methodologies.
-
Service designers and UX professionals interested in creating innovative digital services using human-centered design and iterative prototyping
-
Product managers and innovation leaders responsible for developing, validating, and scaling data-driven service offerings in competitive markets
-
Data scientists and AI engineers seeking to implement machine learning models within service ecosystems, from design to deployment and monitoring
-
Business strategists and consultants advising organizations on digital transformation, business model innovation, or service automation strategies
-
IT architects and digitalization experts working on platform-based solutions, cloud services, or AI-enabled infrastructures in enterprise environments
-
Entrepreneurs and intrapreneurs building new service ventures or transforming existing business models with AI and data-driven approaches
-
Researchers and academics in service systems, digital business, or AI applications exploring the intersection of service design, machine learning, and business innovation
Ready to Join the Full Module?
Book the complete module to benefit from a coherent learning journey across the two certificate courses.