Cloud Machine Learning Engineer with Additional Qualification C++, Basics

Course overview

The training for Cloud Machine Learning Engineer is aimed at individuals who work with AI development and AI engineering in various professional and technical contexts. In many organizations, AI development and AI engineering are integral parts of daily practice, which is why the course repeatedly addresses AI development and AI engineering. Introductory examples illustrate how AI development and AI engineering are embedded in typical areas of responsibility and how requirements related to AI development and AI engineering can be systematically structured. As the content progresses, it explains how AI development and AI engineering are considered in the planning, implementation, and documentation of specific work steps. Participants will see how AI development is applied in various scenarios, while AI engineering serves as a reference point for evaluations or configurations. Several practical sections explicitly address AI development and AI engineering to clarify how decisions regarding AI development and AI engineering impact the overall process. Another focus is on systematically addressing typical questions where AI development and AI engineering must be considered together. It becomes evident how AI development serves as a foundation for certain work steps and how AI engineering is used complementarily to structure or verify results. Participants will have the opportunity to apply AI development and AI engineering in different configurations and reflect on the role of AI development and AI engineering in their respective areas of responsibility. In the next step, it will be brought together how AI development and AI engineering are integrated into long-term developments. It will be shown how insights gained from AI development and information processed with AI engineering can be used for further decisions. Finally, there will be a reflection on how AI development and AI engineering will play a role in future projects and how a conscious approach to AI development and AI engineering 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 will be the focus: 'C++, Basics' provides participants with fundamental knowledge of the C++ programming language. They will learn the basic concepts of object-oriented programming, handling variables, data types, loops, and conditions, as well as the structure and creation of simple C++ programs. Upon completion, participants will be able to write basic programs in C++ and understand the functionality of C++ code.

Upcoming dates

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