결과
당신이 할 수 있는 일
- Choose an architecture based on task and evidence needs.
- Evaluate quality, latency, cost, and safety together.
- Design monitoring and incident response before launch.
먼저 권장사항: AI 기초, 책임 있는 AI 사용자
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커리큘럼
코스 모듈
- 모듈 1
Language-model systems
결과: Reason about tokens, context, generation, and model tradeoffs.
연습: Compare two model options using quality, latency, context, privacy, and cost.
언어 모델 역학모델, 추론 및 제한 사항모델 비용 및 운영 상충관계 - 모듈 3
Agents and tools
결과: Bound multi-step systems with permissions and checkpoints.
연습: Write an agent permission model and failure-recovery path.
Agents, tools, and long-running tasks자동화 경계 및 보호 장치AI 보안 및 오용 위험
캡스톤 적용
AI system design review
Produce an architecture and evaluation plan for a source-grounded AI application.
증거 체크리스트
- Architecture diagram
- Evaluation dataset
- Cost and latency budget
- Security, monitoring, and rollback plan