Customized qualification offers
Enhance your employee’s skills in key digitalization and artificial intelligence (AI) technologies, a crucial requirement for the successful deployment of high-quality software.
In our training courses, we provide a comprehensive overview of basic terms and concepts in the field of digitalization and AI. We explain current developments and methods and illustrate the opportunities available to companies through new software technologies, including which aspects need to be considered when introducing them.
In advanced seminars and workshops, we offer detailed training on specific methods, as well as specialized in-depth knowledge of technologies and tools in the context of key digitalization topics relevant to your company. Through a balanced combination of theoretical concepts and practical applications, you will acquire the skills needed to successfully manage the digital transformation.
You can select the various qualification formats within the focus areas and send us a non-binding inquiry by e-mail.
| Description | Get an introduction to software programs, development processes and machine learning in four parts. | |
| Duration | 1/2 day | 1 day | |
| Target group | People without special IT knowledge | |
| Prerequisites | None | |
| Key-Take-Aways | What are programs? How does machine learning work? How do you create programs? | |
| Description | Define requirements for successful software selection using requirements engineering (RE), one of the key disciplines in the software development process. | |
| Duration | 1/2 | |
| Target group | Interface to SW product development - both in-house and outsourcing | |
| Prerequisites | None | |
| Key-Take-Aways | Forms of RE in practice Requirements documentation with the AMDiRE approach Future topics in RE | |
| Description | Learn first-hand about the latest developments and best practices in software development and how corporate culture can influence the process. | |
| Duration | 1/2 day | 1 day | |
| Target group | SME manager | |
| Prerequisites | None | |
| Key-Take-Aways | Organizational processes Current developments Best practices | |
| Description | Gain a comprehensive understanding of clean code practices to write understandable and maintainable code. | |
| Duration | 1/2 day | 1 day | 3 days | |
| Target group | Software enthusiasts, data scientists, SW developers, engineers | |
| Prerequisites | Basics of Java syntax or similar | |
| Key-Take-Aways | Clean code practices Coding standards through pair programming and code reviews | |
| Description | You will learn about the concepts and different types behind search-based testing in order to subsequently optimize the testing of complex systems. We show how automated testing of automotive systems can be implemented using OpenSBT. | |
| Duration | 1 day | |
| Target group | Test engineers, team leaders | |
| Prerequisites | Experience in developing AI/ML prototypes | |
| Key-Take-Aways | MLOps workflow techniques: GitLab pipelines and Argo workflows, distributed deployment on a Kubernetes cluster | |
| Description | How can an SME with no dedicated UX team quickly do UX research and get impact and value out of it for users? | |
| Duration | 1 h | |
| Target group | SME manager | |
| Prerequisites | none | |
| Key-Take-Aways | Hands-on UX techniques Innovative responses to complex business and social issues by integrating UX techniques | |
| Description | Learn about model-based systems engineering (MBSE) and how it makes the development of complex software-intensive systems more efficient. In the course, you will work on assisted driving functions and validate them with miniature vehicles. In combination with the fundamentals taught, you will gain insights into how design and verification activities can be automated. | |
| Duration | 1 day | |
| Target group | SME Managers, Team Leads | |
| Prerequisites | Basic knowledge of embedded systems | |
| Key-Take-Aways | MbSE basics (methods, languages and tools) Automation of design tasks and verification with models Utilizing potentials in your own company | |
| Description | First, you will get an overview of the history of the development of AI and ML. We will then focus on key concepts, such as deep learning, and discuss possible applications and the future of ML in SMEs with the workshop participants. | |
| Duration | 1/2 day | |
| Target group | SME managers | |
| Prerequisites | None | |
| Key-Take-Aways | Raising awareness of fluctuating developments in AI technology Concepts, developments and algorithms of ML Identifying the potentials and limitations of ML | |
| Description | Deepen your knowledge from a STEM education with the mathematical foundations and basic techniques of machine learning. Get to know a wide range of possible applications and current research results. | |
| Duration | 4 days | |
| Target group | STEM subject graduates | |
| Prerequisites | Mathem. Fundamentals of linear algebra and analysis | |
| Key-Take-Aways | Applications Practical examples and programming tutorials Concepts, methods and algorithms of ML | |
| Description | You will receive a targeted overview of the topic of artificial intelligence (AI) and related disciplines such as machine learning in interactive, approx. 90-minute webinar sessions. | |
| Duration | 5 days of 90 minutes each as a webinar | |
| Target group | Decision-makers from technical disciplines of companies in mechatronics and automation | |
| Prerequisites | None | |
| Key-Take-Aways | Overview of AI and ML Recognize AI potential independently Enabling skills about AI (concepts - techniques - solutions) | |
| Description | Learn how machine learning is used to generate deep fakes and how they can be recognized. |
| Duration | 1h |
| Target group | everyone |
| Prerequisites | none |
| Key-Take-Aways | Raising awareness of the issue of artificially generated data Examples of deep fakes Recognition strategies |
| Description | Gain an insight into the central challenges of using AI systems and how human skills and abilities can be combined with AI strengths in a targeted manner. |
| Duration | 1h |
| Target group | everyonr |
| Prerequisites | none |
| Key-Take-Aways | Approaches for effective collaboration between humans and AI AI as decision support |
| Description | Learn how important it is to clearly align AI projects with user needs so that they do not become expensive disappointments. |
| Duration | 1h |
| Target group | everyone |
| Prerequisites | none |
| Key-Take-Aways | Limits of AI applications User-centered design as a basic prerequisite for benefiting from technological progress |
| Description | Get to know the techniques of an MLOps workflow and apply them hands-on for the transition from a Jupyter notebook to a productive AI system. |
| Duration | 1/2 day | 1 day | 3 days |
| Target group | SW developers, data scientists, engineers |
| Prerequisites | Experience in developing AI/ML prototypes |
| Key-Take-Aways | MLOps workflow techniques: GitLab pipelines and Argo workflows, distributed deployment on a Kubernetes cluster |
| Description | In a short interactive presentation, you will gain an insight into intelligent heat/cold storage for energy-efficient buildings. | |
| Duration | 1h | |
| Target group | SME managers | |
| Prerequisites | none | |
| Key-Take-Aways | Current findings and methods for AI applications for energy storage | |
| Description | Get an overview of the various renewable energy sources, the technology for recording consumption and the use of the information in the context of energy management systems. | |
| Duration | 1h | |
| Target group | SME managers, Those interested in energy management | |
| Prerequisites | None | |
| Key-Take-Aways | Overview of energy management and renewable energies Current findings and methods | |
| Description | Generate new knowledge about sustainable cross-building energy management in neighborhoods and learn how to use the fortiss planning tool. | |
| Duration | 1/2 day | |
| Target group | Engineers, SME managers, employees of planning offices | |
| Prerequisites | None | |
| Key-Take-Aways | Opportunities of sector coupling Control and architectures for the smart grid Open source planning and simulation environment from fortiss | |
| Description | In a short interactive presentation, you will gain an insight into intelligent heat/cold storage for energy-efficient buildings. | |
| Duration | 1h | |
| Target group | SME managers, Energy supply and construction industry | |
| Prerequisites | None | |
| Key-Take-Aways | Current findings and methods for AI applications for energy storage systems | |
| Description | Learn how to build a smart, intelligent and portable solar power generator with monitoring and control functions from readily available components. | |
| Duration | 1/2 day | |
| Target group | People interested in solar energy | |
| Prerequisites | None | |
| Key-Take-Aways | Ability to build solar box independently Versatile solar box | |
| Description | Get an introduction to Distributed Ledger Technologies (DLT), which includes blockchain, and the associated technology landscape. Following on from this, you will get to know a three-step method: Needs analysis, feasibility evaluation and IT architecture design of specific use cases. | |
| Duration | 1/2 day | |
| Target group | SME managers | |
| Prerequisites | None | |
| Key-Take-Aways | Overview DLT Practical examples Opportunities and challenges | |
| Description | Let our experts systematically introduce you to data-supported process engineering and identify process and system deficiencies in your own company. | |
| Duration | 1/2 day | 1 day | 3 days | |
| Target group | SMEs from the manufacturing industry with a desire for digitalization | |
| Prerequisites | None | |
| Key-Take-Aways | Digitization possibilities based on application examples Method toolbox for problem analysis | |
| Description | Get an overview of how industrial edge and cloud technologies provide more flexibility, scalability and security in data processing and thus create the basis for new business models. | |
| Duration | 1h | 2h | |
| Target group | Engineers, software developers | |
| Prerequisites | None | |
| Key-Take-Aways | IIoT, Edge and Cloud in networked production IIoT use cases and industry examples Open-source solutions | |
