1z0-1110-23試験無料問題集（80題）「Oracle Cloud Infrastructure Data Science 2023 Professional 認定」

出題：1

What preparation steps are required to access an Oracle AI service SDK from a Data Science notebook session?

A. Create and upload score.py and runtime.yaml.

B. Import the REST API.

C. Call the ADS command to enable AI integration

D. Create and upload the APIsigning key and config file.

正解：D 解答を投票する

出題：2

Which two statements are true about published conda environments?

A. They are curated by Oracle Cloud Infrastructure (OCI) Data Science.

B. The odac conda init command is used to configure the location of published conda environments.

C. Your notebook session acts as the source to share published conda environments with team members.

D. You can only create a published conda environment by modifying a Data Science conda environment.

E. In addition to service job run environment variables, conda environment variables can be used in Data Science Jobs.

正解：C,E 解答を投票する

出題：3

You are attempting to save a model from a notebook session to the model catalog by using the Accelerated Data Science (ADS) SDK, with resource principal as the authentication signer, and you get a 404 authentication error. Which two should you look for to ensure permissions are set up correctly?

A. The model artifact is saved to the block volume of the notebook session.

B. The networking configuration allows access to Oracle Cloud Infrastructure services through a Service Gateway.

C. The policy for a dynamic group grant manages permissions for the model catalog in it compartment.

D. A dynamic group has rules that matching the notebook sessions in it compartment.

E. The policy for your user group grants manages permissions for the model catalog in this compartment.

正解：D,E 解答を投票する

出題：4

You have trained three different models on your data set using Oracle AutoML. You want to visualize the behavior of each of the models, including the baseline model, on the test set. Which class should be used from the Accelerated Data Science (ADS) SDK to visually compare the models?

A. EvaluationMetrics

B. ADSEvaluator

C. ADSExplainer

D. ADSTuner

正解：B 解答を投票する

出題：5

You have just completed analyzing a set of images by using Oracle Cloud Infrastructure (OCI) Data Labelling, and you want to export the annotated data. Which two formats are supported?

A. CONLL V2003

B. Data Labelling Service Proprietary JSON

C. Spacy

D. COCO

正解：C,D 解答を投票する

出題：6

You are creating an Oracle Cloud Infrastructure (OCI) Data Science job that will run on a recurring basis in a production environment. This job will pick up sensitive data from an Object Storage bucket, train a model, and save it to the model catalog.
How would you design the authentication mechanism for the job?

A. Store your personal OCI config file and keys in the Vault and access the Vault through the job run resource principal.

B. Use the resource principal of the job run as the signer in the job code, ensuring there is a dynamic group for this job run with appropriate access to Object Storage and the model catalog.

C. Create a pre-authenticated request (PAR) for the Object Storage bucket, and use that in the job code.

D. Package your personal OCI config file and keys in the job artifact

正解：B 解答を投票する

出題：7

You want to write a Python script to create a collection of different projects for your data science team. Which Oracle Cloud Infrastructure (OCI) Data Science interface would you use?

A. Command line interface (CLI)

B. OCI Console

C. Mobile App

D. The OCI Software Development Kit (SDK)

正解：D 解答を投票する

出題：8

In the Oracle Cloud Infrastructure (OCI) Data Science service, how does Model Catalog help with model deployment and management in MLOps?

A. It helps to package the model and its dependencies into a lightweight, portable container.

B. It provides a centralized and scalable way to manage models and their metadata.

C. It is a database that stores all the features used in a machine learning model.

D. It helps to automate the feature engineering process.

正解：B 解答を投票する

1z0-1110-23試験無料問題集「Oracle Cloud Infrastructure Data Science 2023 Professional 認定」