Which AWS service gives access to many foundation models from multiple providers through one API?
Q2easymcq
Which service is for building, training, and deploying fully custom ML models?
Q3easymcq
What is SageMaker JumpStart?
Q4easymcq
Which AWS offering is an agentic IDE (development environment), not a chat assistant?
Q5easymcq
Which service is GenAI-powered business intelligence/analytics evolved from QuickSight?
Q6easymcq
What is Bedrock AgentCore?
Q7easymcq
Which of these is an open-source SDK for building AI agents with a model-driven approach?
Q8easymcq
Which is NOT a benefit of using AWS-managed GenAI services vs. building your own infrastructure?
Q9easymcq
Provisioned throughput vs. on-demand token pricing is mainly a tradeoff between:
Q10easymcq
Why might not every FM be available in every AWS Region?
Q11hardmcq
A team wants to deploy an open-source pre-trained model quickly into their own SageMaker environment with minimal setup. Best fit?
Q12hardmulti
Which of the following are genuine advantages of using AWS's managed GenAI services over self-built infrastructure?
Select all that apply.
Q13hardmcq
A high-volume, steady, latency-sensitive production workload is best matched to:
Q14hardordering
Order these from 'least custom effort, fastest to ship' to 'most custom effort, most differentiated'.
1.Fine-tune a custom model on SageMaker AI
2.Deploy a pre-built model via SageMaker JumpStart
3.Call a foundation model directly via Bedrock
Q15hardmatching
Match each AWS offering to its primary purpose.
Bedrock AgentCore
Strands Agents
Kiro
Amazon Quick
Q16hardmcq
A regulated healthcare company needs its GenAI infrastructure to inherit AWS's compliance certifications and encryption/IAM controls automatically. This describes which category of benefit?
Q17hardmcq
Which best distinguishes Amazon Bedrock from SageMaker AI?
Q18hardmulti
Which factors should influence a Region/deployment choice for a GenAI workload?
Select all that apply.
Q19hardmcq
A startup with unpredictable, spiky GenAI traffic and a tight budget should generally start with:
Q20hardmcq
Which AWS product name is most likely to appear as a distractor confused with 'Amazon Q' on the exam, despite being a completely separate BI/analytics product?