AI Management in the Cloud

Course overview

AI with a focus on management in the cloud 1. Introduction to AI Management in the Cloud: Definition and advantages of cloud-based AI management, overview of cloud providers and their offerings, role of the cloud in digital transformation 2. Cloud Architectures for AI Applications: Comparison of different cloud architectures, best practices for developing AI apps in the cloud, security and privacy aspects 3. Implementation of AI Solutions in the Cloud: Steps for migrating existing AI applications, integration of cloud services into business processes, pilot projects and evaluation 4. Management of Cloud Resources for AI: Optimization of cloud costs and resources, monitoring and performance management, scaling and flexibility in the cloud 5. Ethics and Compliance in Cloud-based AI Management: Security and privacy policies, ethical challenges in the cloud, regulatory requirements and their implementation 6. Success Measurement of Cloud AI Projects: KPIs and metrics for cloud AI initiatives, evaluation of cloud performance, feedback mechanisms for improvement 7. Practical Project: Developing a Cloud AI Solution: Development of a prototype for a cloud AI application, presentation of results and feedback, iterative improvement of the project 8. Future Perspectives of AI Management in the Cloud: Latest trends and technologies in cloud AI management, preparation for future challenges, strategies for continuous education

Upcoming dates

• 2026-07-29T22:00:00.000Z · 2027-09-26T22:00:00.000Z · Virtuelles Klassenzimmer
• 2026-07-30T22:00:00.000Z · 2027-09-26T22:00:00.000Z · Virtuelles Klassenzimmer
• 2026-08-02T22:00:00.000Z · 2027-03-14T23:00:00.000Z · München · Combined Learning
• 2026-08-03T22:00:00.000Z · 2027-09-29T22:00:00.000Z · München · Combined Learning
• 2026-08-12T22:00:00.000Z · 2027-03-24T23:00:00.000Z · München · Combined Learning