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Oracle 1Z0-1110-26 Exam Syllabus Topics:

Oracle Cloud Infrastructure Data Science Professional Sample Questions:

1. Select two reasons why it is important to rotate encryption keys when using Oracle Cloud Infrastructure (OCI) Vault to store credentials or other secrets.

A) Key rotation allows you to encrypt no more than five keys at a time
B) Periodically rotating keys limits the amount of data encrypted by one key version
C) Periodically rotating keys makes it easier to reuse keys
D) Key rotation improves encryption efficiency
E) Key rotation reduces risk if a key is ever compromised

2. You have built a machine model to predict whether a bank customer is going to default on a loan. You want to use Local Interpretable Model-Agnostic Explanations (LIME) to understand a specific prediction. What is the key idea behind LIME?

A) Local explanation techniques are model-agnostic, while global explanation techniques are not
B) Global and local behaviours of machine learning models are similar
C) Model-agnostic techniques are more interpretable than techniques that are dependent on the types of models
D) Global behaviour of a machine learning model may be complex, while the local behaviour may be approximated with a simpler surrogate model

3. Which Oracle Cloud Infrastructure (OCI) Data Science policy is invalid?

A) Allow dynamic-group DataScienceDynamicGroup to manage data-science-projects in compartment DataScience
B) Allow group DataScienceGroup to use virtual-network-family in compartment DataScience
C) Allow dynamic-group DataScienceDynamicGroup to manage data-science-family in compartment DataScience
D) Allow group DataScienceGroup to use data-science-model-sessions in compartment DataScience

4. You realize that your model deployment is about to reach its utilization limit. What would you do to avoid the issue before requests start to fail? Pick THREE.

A) Reduce the load balancer bandwidth limit so that fewer requests come in
B) Delete the deployment
C) Update the deployment to use fewer instances
D) Update the deployment to add more instances
E) Update the deployment to use a larger virtual machine (more CPUs/memory)

5. Which stage in the machine learning life cycle helps in identifying the imbalance present in the data?

A) Data Access
B) Data Exploration
C) Data Modeling
D) Data Monitoring

Solutions: