Cloud AI Specialist for AI Deployment

Course overview

Cloud AI specialists bring AI applications into productive use via cloud services: They select appropriate services, configure them securely, and ensure stable operation. The training covers the path from a proven use case to the deployed AI solution in cloud environments. Overview of Cloud Services for AI The major platforms offer comparable components with their own specifics. - Categorize AI services from popular cloud providers like Microsoft Azure, AWS, and Google Cloud - Understand language models, search, and document services as components - Selection criteria: data location, costs, contractual situation, existing IT landscape Deployment of AI Applications - From local testing to operational deployment - Configuration of accesses, keys, and environments - Integration with existing applications via interfaces - Staging concept: test changes first, then go live Operation and Cost Control Cloud operation is ongoing work, not a one-time switch. - Monitor availability, response times, and error rates - Understand, budget, and limit usage-dependent costs - Adjust capacities and quotas to usage - Controlled adoption of updates for models and services Security and Data Protection in the Cloud - Access concepts, roles, and rights for AI services - Handling personal and confidential data in cloud services - Logging and traceability of processing - Keep agreements on order processing in mind Collaboration within the Company - Translate requirements from specialist departments into deployment decisions - Coordinate with IT security, data protection, and procurement - Operational documentation and contact person for disruptions Architectural Patterns for Cloud AI Recurring patterns facilitate design and communication. - Direct connection, intermediary layer, and queues as basic patterns - Separation of testing, acceptance, and production environments - Plan failure behavior: what happens if the AI service does not respond - Documented architectural decisions for later traceability - Consider regions and availability zones when selecting services - Exit capability: think about alternative paths and data export from the beginning - Understand the division of responsibility with the provider: what the service provides, what remains with the company This training conveys how AI applications can be securely deployed, economically operated, and anchored within the company through cloud services.

Upcoming dates

• 2026-10-20T22:00:00.000Z · 2026-12-22T23:00:00.000Z · Virtuelles Klassenzimmer
• 2026-10-20T22:00:00.000Z · 2026-12-22T23:00:00.000Z · Frankfurt am Main · Hybrid Learning
• 2026-10-20T22:00:00.000Z · 2026-12-22T23:00:00.000Z · Herzogenrath · Hybrid Learning
• 2026-10-20T22:00:00.000Z · 2026-12-22T23:00:00.000Z · Leinfelden-Echterdingen · Hybrid Learning
• 2026-11-03T23:00:00.000Z · 2027-07-03T22:00:00.000Z · Virtuelles Klassenzimmer