AI Security

Course overview

AI Security deals with attacks on models and the damage that models themselves can cause. AI Security complements traditional IT security with model-specific attack vectors. Course Content 1. Attack Vectors on Models Manipulated Inputs Poisoned Training Data Inference on Training Content 2. AI Security in Applications Filtering Inputs and Outputs Limiting Rights of Model Tools Separation of Instruction and Content 3. Operational Safeguarding Access to Models and Keys Logging of Requests Detection of Misuse 4. Evaluation Testing Before Deployment Recurring Reevaluation Proof to Certification Bodies Professional Relevance AI Security becomes an operational issue with every model used productively Traditional protective measures do not apply to model-specific attacks The profile connects security work with model understanding

Upcoming dates

• 2026-11-01T23:00:00.000Z · 2027-04-09T22:00:00.000Z · Virtuelles Klassenzimmer
• 2026-11-01T23:00:00.000Z · 2027-09-16T22:00:00.000Z · Virtuelles Klassenzimmer
• 2026-11-01T23:00:00.000Z · 2027-04-09T22:00:00.000Z · Berlin · Combined Learning
• 2026-11-01T23:00:00.000Z · 2027-09-16T22:00:00.000Z · Berlin · Combined Learning
• 2026-11-01T23:00:00.000Z · 2027-04-09T22:00:00.000Z · München · Combined Learning

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