LLM Application Security — Building AI Features Safely

A twenty-hour, highly interactive mid-level course where you secure an AI assistant along a live LLM-application pipeline — treating the model as untrusted, assuming prompt injection can succeed, containing an agent's blast radius, and building so a manipulated model can do little harm. Four hands-on activities in every lesson.

What you'll learn

• Treat the model as an untrusted component and reason about LLM security along the application pipeline.
• Defend against direct and indirect prompt injection by containing its impact, not relying on prevention.
• Handle untrusted input and output, contain an agent's blast radius, and protect data across the pipeline.
• Layer guardrails, threat-model and securely develop LLM features, and operate them securely over time.

Sign in to enrol — you can pay by bKash or Nagad, or apply a promo code.