The CAS Systems Engineering offers advanced training in complex system description, development and verification for engineers. At the same time, it prepares engineers for leading roles within increasingly interdisciplinary and complex system tasks.
Contents
– Systems & Requirements Engineering Basics – Model Based Systems Engineering – Digital Transformation & Systems Engineering – Project Management & Lean Methods for Systems Engineering – Intellectual Property Basics – Quality Assurance & Systems Engineering – Systems Engineering Project
There is a possibility to take courses at our partner SE-Training during the course of the CAS: – Design Thinking and Lean Innovation Advanced – MBSE & SYSML Intermediate – Systems Reliability – Acoustics Systems Engineering – Configuration Management.
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Januar 2026
November 2026
in revision
9 months
CHF 7'900.-
inc. registration fee and study materials in digital form
Certificate of Advanced Studies Hochschule Luzern/FHZ in Systems Engineering
CAS
12
216
Horw
08:30 - 17.00 h
Graduated as an engineer or in natural science at university level, work in the field of engineering, would like to step up and be responsible for larger systems.
University (incl. University of Applied Sciences) level graduation in engineering or natural science and a minimum of 2 years practical experience. Persons with a degree in higher vocational education and training must have at least two years of professional experience in a field relevant to this continuing education and training. At latest at the end of this program they must have the appropriate scientific knowledge in the field of this program. Persons without a tertiary degree will only be admitted in exceptional cases in a sur-dossier procedure. Please refer to the Studienreglement for more detailed information.
Engineering and ArchitectureContinuing EducationInstitute of Mechanical Engineering and Energy Technology IMEComputer Science and Information Technology
SE Training GmbH
The CAS sessions are divided into formal lessons and group work so that you can start to implement the delivered topics into practice.
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(115.9 KB) .PDF
MAS Agile DevOps & Cloud Transformation
MAS Data Engineering and Data Science
MAS Machine Learning
