Oracle 1Z0-1110-26 Certification Sample Questions and Answers

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Oracle 1Z0-1110-26 Sample Questions:

01. An administrator is writing the first IAM policy for a tenancy that will run OCI Data Science, and wants a single statement to cover projects, notebook sessions, models, jobs and model deployments.
What does the aggregate resource type data-science-family identify in that statement?
a) The compute shapes that notebook sessions and jobs are permitted to be created on.
b) The set of users and groups that are permitted to open a notebook session.
c) Every Data Science resource type under one name.
d) The compartment that the Data Science resources are created in.
 
02. In a retrieval-augmented application built with ADS on OCI Data Science, a question arrives, the retriever selects the passages that match it, and a request is then sent to OCI Generative AI.
Which part of the application combines the question and the retrieved passages into that request?
a) The vector store, which holds the embeddings and assembles them for each query.
b) The chain, which binds retrieval to the model call.
c) The model deployment, which rewrites each incoming payload before forwarding it.
d) The embedding step, which converts the question and the passages into one input.
 
03. A product recommendation endpoint is nearly idle for most of the day and then takes a thirty-fold rise in traffic during two one-hour promotional windows. The team runs a fixed instance count sized for those windows and has been asked to defend or change that choice on cost grounds.
Which assessment of the current configuration is correct?
a) The fixed count is the cheaper arrangement, as autoscaling keeps every instance it has started available in readiness for the next window.
b) Moving to autoscaling would hold the deployment's cost constant across the whole day.
c) The choice makes no difference, since both arrangements provision the same capacity during the promotional windows.
d) Capacity sized for the peak is provisioned around the clock, so autoscaling would instead track the load actually served.
 
04. Before a model card is published, a reviewer checks how its feature importance ranking was produced and finds that the columns were permuted over the same records the model was fitted on.
Why should the ranking be recomputed on held-out records first?
a) Permutation importance needs data that has been through the same transformations as the training data, and the held-out split is the only one guaranteed to have been transformed consistently.
b) Importances measured on the fitted records reflect structure the model memorized rather than what drives unseen predictions.
c) Training records carry the target column, which permutation importance is not permitted to read.
d) The held-out split contains more records than the training split, so a ranking estimated from it is the more stable of the two.
 
05. A team saves a LangChain application to the Model Catalog so that it can be deployed. The entry comes out with no hyperparameters, no training metrics and a taxonomy naming no framework, and a reviewer asks whether the save went wrong.
How should the team respond?
a) Re-save the entry with the taxonomy completed, since a catalog entry has to name the framework a model was built with.
b) Keep the application outside the catalog, since the catalog holds trained models only.
c) Fine-tune a foundation model so the entry has metrics to carry.
d) Nothing in the application was fitted, so there are no learned parameters or training scores to record, and the entry is complete as it stands.
 
06. Which Accelerated Data Science (ADS) class runs a hyperparameter search over an estimator that the data scientist has already selected?
a) ADSEvaluator
b) ADSTuner
c) DatasetBrowser
d) DataFrameLabelEncoder()
 
07. A network-operations group is fitting a single scikit-learn estimator over several hundred million fault records. The work is not a Spark workload, and the notebook session the team develops in cannot hold the full dataset in memory.
How should the team organize development and the full training run?
a) Keep the whole dataset in the session on the largest shape they can obtain.
b) Cut the dataset down permanently to the sample the current session holds, because a model fitted on a sample generalizes as well as one fitted on everything.
c) Iterate on a sample inside the notebook session and submit the full fit as a job on infrastructure sized for it.
d) Submit the training to a Data Flow application so that the fit is spread across a managed Spark cluster.
 
08. An analyst has one operator run working over a single region's readings and must now produce the same outputs for eleven more regions. Each region keeps its readings in its own location and needs its own horizon.
What does producing those additional runs involve?
a) Supplying a configuration per region that names its input, its parameters and its output location.
b) Rebuilding the work as a notebook workflow, because an operator is bound to the one dataset it was first run against.
c) Registering each region in the service as its own operator before any of its runs can be configured.
d) Editing the operator so that it loops over the twelve regions in one run.
 
09. Which TWO of the following are stages of the AI Quick Actions workflow in an OCI Data Science notebook session?
(Choose two.)
a) Exploring the foundation models available in the notebook session
b) Defining a custom MQL metric for a deployment
c) Publishing a conda environment
d) Evaluating a model
e) Labeling images
 
10. Four data scientists in one project each work in their own notebook session on CPU shapes. One of them now has to fine-tune a deep learning model that needs an accelerator, while the other three continue exploratory work that runs comfortably as it is.
What is the appropriate change?
a) Give that one scientist a notebook session on a GPU shape.
b) Create a second project configured for GPU work, since a project fixes the shape of the sessions inside it.
c) Deactivate all four sessions and activate them again on a GPU shape, so that the project stays consistent.
d) Raise a request to add GPU capacity to the running session, as a session's shape cannot be changed.

Answers:

Question: 01

Answer: c

Question: 02

Answer: b

Question: 03

Answer: d

Question: 04

Answer: b

Question: 05

Answer: d

Question: 06

Answer: b

Question: 07

Answer: c

Question: 08

Answer: a

Question: 09

Answer: a, d

Question: 10

Answer: a

 

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