Applied AI in Service Systems
Certificate Course - Information Systems Engineering - ISE.5.3DS.I26
| Date | Nov 3 - 5, 2027 |
| Duration | 3 days |
| Location | On campus - Karlsruhe |
| Language | English |
| ECTS | upon request |
| Cost | 2,050€ |
Fundamentals
The course covers AI and machine learning fundamentals for analytical services in digital service systems.
Technology
It focuses on supervised machine learning and the full lifecycle of AI-based analytical services.
Applications
Students develop analytics-based digital services through hands-on work in collaborative service system scenarios.
What you'll explore
- Motivation, Terminology, Overview
- Learning along a Digital Service Lifecycle
- Initiation
- Performance estimation & evaluation
- Deployment
- Concept drift
- Learning in Service Systems:
- Meta Learning
- Transfer Learning
- Ethics of AI
Your key takeaways
Participants
- understand the importance of analytics (supported by AI and Machine Learning) for digital services
- comprehend the notion of service systems and business networks
- understand the importance and the means of applying AI and Machine Learning within service systems
- are able to comprehend and implement the complete lifecycle of a typical Artificial Intelligence use case with supervised machine learning
- gain an understanding of analytical collaboration between independent entities and how they can derive insights.
- are familiar with the concepts of system-wide learning, transfer machine learning, meta machine learning, and concept drift
- are proficient with basic, typical Python code for AI challenges.
Taught by recognized experts in Applied AI in Service Systems
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.
Joshua Holstein
Joshua Holstein, M.Sc. is a doctoral researcher at Karlsruhe Institute of Technology (KIT) specializing in human-AI collaboration and intelligent decision support systems. His work focuses on designing AI systems that improve decision-making through uncertainty communication, explainability, and incentive alignment. He investigates how humans form mental models of AI and how this influences trust and performance. Combining behavioral experiments and design science, he develops frameworks that enhance collaborative intelligence while preventing overreliance and misinformation in AI-supported environments.
Who should attend
This course is particularly beneficial for professionals in the following fields:
-
Data scientists and machine learning engineers
Practitioners building AI models who want to apply supervised learning across the full lifecycle of analytics-based digital services. -
Product managers and AI product owners
Professionals defining AI use cases, metrics, and deployment strategies in service systems, from initiation to monitoring and concept drift handling. -
Service designers and digital service innovators
Experts integrating AI into customer-centric services and business networks, focusing on value creation and responsible use of AI. -
IT architects and MLOps engineers
Professionals designing data pipelines, model deployment, monitoring, and collaboration setups for AI services across organizational boundaries. -
Business analysts and data-driven decision-makers
Specialists translating business needs into analytical solutions and evaluating model performance, explainability, and impact in practice. -
Consultants and transformation leaders
Advisors guiding organizations on AI adoption, governance, ethics, and scaling analytical services in complex service ecosystems. -
Researchers and early-career academics
Researchers, PhD candidates, and academic staff interested in applied ML, human–AI collaboration, transfer/meta learning, and AI in service systems.
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.
About HECTOR School
HECTOR School, the Technology Business School of the Karlsruhe Institute of Technology (KIT), is a leading provider of executive education in technology-driven fields.
For this course, participants who successfully complete the examination can earn a KIT certificate with ECTS credits, which may be credited toward our Executive Master of Science or Advanced Studies Programs, subject to content alignment.