Module: Machine Learning for Data-Driven Decision Making
This certificate module combines three complementary short courses in a structured learning path.
Participants build a broad understanding of machine learning for decision-making, from foundational models and learning principles to financial machine learning techniques and advanced kernel and Bayesian methods.
General Information
| Dates | May 31 - Jun 11, 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 three 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 Machine Learning
Applied financial machine learning methods using Python for prediction and volatility analysis.
| Date | May 31 - Jun 2 and 7 - 9, 2027 |
| Duration | 6 days (Mo. to Wed. and Mo. to Wed. next week) |
Machine Learning for Decision Makers
Introduction to machine learning models, learning principles, and decision-oriented analytical methods.
| Date | Jun 3 - 4, 2027 |
| Duration | 2 days |
Kernel and Bayesian Methods in Machine Learning
Advanced kernel and Bayesian methods for data description, semi-parametric forecasting, and probabilistic reasoning.
| Date | Jun 10 - 11, 2027 |
| Duration | 2 days |
How the Courses Fit Together
Participants first build a foundation in machine learning models and learning principles, then explore financial machine learning techniques for forecasting and market analysis, and finally deepen their knowledge through kernel and Bayesian methods.
Who should attend
This module is designed for professionals seeking a structured introduction to machine learning for data-driven decision-making, with a focus on practical applications, model deployment, and business impact.
- Data scientists and machine learning engineers interested in building, optimizing, and deploying predictive models for real-world business applications.
- Business analysts and decision-makers looking to integrate data-driven insights into strategic planning, operational efficiency, or customer experience enhancement.
- Product managers and innovation leaders responsible for developing AI-powered products or services that leverage predictive analytics and automation.
- IT professionals and software developers integrating machine learning models into applications, workflows, or enterprise systems for actionable outcomes.
- Risk managers and financial analysts using predictive modeling for risk assessment, fraud detection, or financial forecasting.
- Marketing and sales professionals employing data-driven approaches for customer segmentation, personalization, and campaign optimization.
- Researchers and academics exploring the intersection of machine learning, decision theory, and real-world applications in business and industry.
Ready to Join the Full Module?
Book the complete module to benefit from a coherent learning journey across all three certificate courses.