AI Automation Developer

Course overview

An AI Automation Developer connects AI models with automation logic to independently execute repetitive tasks. This training provides knowledge on how to build such automations from the idea to operational status, including points where human oversight remains sensible. Identifying Automation Potential Not every task is equally suitable for automation. - Identify and evaluate repetitive tasks - Realistically compare the effort and benefits of automation - Simplify and clean processes before automation Designing Automation Processes - Connect triggering events, verification conditions, and subsequent actions into a process - Intentionally integrate AI steps at appropriate points in the process - Plan interfaces to existing systems and data sources - Cleanly translate data formats between individual steps Stably Operating Processes - Recognize and automatically handle error cases - Log results and make them traceable - Adjust processes to changing requirements - Keep execution times and resource needs in mind Clarifying Control and Responsibility Automation relieves but does not replace every decision. - Identify points in the process where human approval remains necessary - Clarify responsibilities for decisions made automatically - Establish escalation paths for errors or uncertainties - Ensure traceability of automated decisions Further Developing Automations - Gradually expand existing processes with new steps - Use results from ongoing operations for optimization - Document processes to ensure they remain traceable within the team - Anchor knowledge about automations within the team Embedding Data Protection and Compliance in Automations Automated processes often handle personal data. - Check data protection requirements for each automation step - Implement data minimization in automated processes - Technically consider deletion concepts and retention periods - Prepare documentation for internal and external audits Classifying Tools and Platforms - Differentiate common automation platforms by purpose - Weigh low-code approaches against programmed solutions - Evaluate connection options to AI services for each platform - Consider switching costs and dependencies when choosing a platform This training demonstrates how AI-supported automation reliably and transparently relieves workflows.

Upcoming dates

• 2026-10-20T22:00:00.000Z · 2026-12-22T23:00:00.000Z · Virtuelles Klassenzimmer
• 2026-11-03T23:00:00.000Z · 2027-07-03T22:00:00.000Z · Virtuelles Klassenzimmer
• 2026-11-17T23:00:00.000Z · 2027-01-19T23:00:00.000Z · Virtuelles Klassenzimmer
• 2026-12-01T23:00:00.000Z · 2027-08-01T22:00:00.000Z · Virtuelles Klassenzimmer