Cloud Machine Learning Engineer with Additional Qualification in Accessibility Fundamentals

Course overview

The training for Cloud Machine Learning Engineer is aimed at individuals who work with automation and Large Language Models (LLM) in various professional and technical contexts. In many organizations, automation and Large Language Models (LLM) are integral parts of daily practice, which is why the course repeatedly addresses automation and Large Language Models (LLM). Introductory examples demonstrate how automation and Large Language Models (LLM) are embedded in typical areas of work and how requirements related to automation and Large Language Models (LLM) can be systematically structured. As the content progresses, it explains how automation and Large Language Models (LLM) are considered in the planning, implementation, and documentation of specific work steps. Participants will see how automation is used in various scenarios, while Large Language Models (LLM) serve as a reference point for evaluations or configurations. Several practical sections explicitly address automation and Large Language Models (LLM) to clarify how decisions regarding automation and Large Language Models (LLM) impact the overall process. Another focus is on systematically addressing typical questions where automation and Large Language Models (LLM) must be considered together. It becomes evident how automation serves as a foundation for certain work steps and how Large Language Models (LLM) are used complementarily to structure or verify results. Participants will have the opportunity to apply automation and Large Language Models (LLM) in different configurations and reflect on the role of automation and Large Language Models (LLM) in their respective areas of responsibility. In the next step, it will be brought together how automation and Large Language Models (LLM) are integrated into long-term developments. It will be shown how insights gained from automation and information processed with Large Language Models (LLM) can be used for further decisions. Finally, there will be a reflection on how automation and Large Language Models (LLM) will play a role in future projects and how a conscious approach to automation and Large Language Models (LLM) contributes to making processes understandable and transparent. Agenda: 1. Classification of roles and areas of responsibility 2. Overview of typical work processes 3. Structuring of professional and technical requirements 4. Approaches to analysis, planning, and implementation 5. Use of supporting tools and platforms 6. Documentation and traceability of workflows 7. Collaboration with adjacent roles and areas 8. Long-term development of structures and processes At the end of the training, the following module is the focus: "Accessibility fundamentals" imparts basic knowledge and skills in the area of accessibility to the participants. Participants will learn how to design digital content and applications to be accessible to all users, including people with disabilities.

Upcoming dates

• 2026-09-06T22:00:00.000Z · 2027-03-09T23:00:00.000Z · Eschborn, Taunus · Combined Learning
• 2026-09-06T22:00:00.000Z · 2027-03-09T23:00:00.000Z · München · Combined Learning
• 2026-09-06T22:00:00.000Z · 2026-12-07T23:00:00.000Z · München · Combined Learning
• 2026-09-06T22:00:00.000Z · 2026-12-07T23:00:00.000Z · Eschborn, Taunus · Combined Learning