Oracle 1Z0-1110-25 Online Practice Questions and Exam Preparation

Oracle 1Z0-1110-25 Online Questions & Answers

• Question 151:

  Which OCI Data Science interaction method can function without the need of scripting?

  A. OCI Console
  B. CLI
  C. Language SDKs
  D. REST APIs
  A. OCI Console

• Question 152:

  You're going to create an Oracle Cloud Infrastructure Anomaly Detection model for multivariate data. Where do you need to store the training data?

  A. Your local machine
  B. MySQL database
  C. Autonomous Data Warehouse
  D. Object Storage Bucket
  D. Object Storage Bucket

• Question 153:

  You have just started as a data scientist at a healthcare company. You have been asked to analyze and improve a deep neural network model, which was built based on the electrocardiogram records of patients. There are no details about the model framework that was built. What would be the best way to find more details about the machine learning models inside the model catalog?

  A. Refer to the code inside the model
  B. Check for model taxonomy details
  C. Check for metadata tags
  D. Check for provenance details
  D. Check for provenance details

• Question 154:

  You want to build a multistep machine learning workflow by using the Oracle Cloud Infrastructure (OCI) Data Science Pipeline feature. How would you configure the conda environment to run a pipeline step?

  A. Configure a compute shape
  B. Configure a block volume
  C. Use command-line variables
  D. Use environmental variables
  D. Use environmental variables

• Question 155:

  In machine learning, what is the primary difference between supervised and unsupervised learning?

  A. Supervised learning involves data that has been labeled and classified, while unsupervised learning data is unlabeled and unclassified.
  B. Supervised learning is monitored closely by data scientists, while they don't play a role inunsupervised learning.
  C. Supervised learning is only used for image recognition, while unsupervised learning can be used for various analytics applications.
  D. Supervised learning is created and managed by the Data Engineer.
  A. Supervised learning involves data that has been labeled and classified, while unsupervised learning data is unlabeled and unclassified.

• Question 156:

  What is the correct definition of Git?

  A. Git is a centralized version control system that allows you to revert to previous versions of files as needed.
  B. Git is a distributed version control system that allows you to track changes made to a set of files.
  C. Git is a distributed version control system that protects teams from simultaneous repo contributions and merge requests.
  D. Git is a centralized version control system that allows data scientists and developers to track copious amounts of data.
  B. Git is a distributed version control system that allows you to track changes made to a set of files.

• Question 157:

  Which of the following programming languages are most widely used by data scientists?

  A. C and C++
  B. Python, R, and SQL
  C. Java and JavaScript
  B. Python, R, and SQL

• Question 158:

  You have an embarrassingly parallel or distributed batch job with a large amount of data running using Data Science Jobs. What would be the best approach to run the workload?

  A. Create a job in Data Science Jobs and then start the number of simultaneous job runs required for your workload
  B. Create a new job for every job run that you have to run in parallel, because the Data Science Job service can have only one job per job
  C. Create the job in Data Science Jobs and start a job run. When it is done, start a new job run until you achieve the number of runs required
  D. Reconfigure the job run because Data Science Jobs does not support embarrassingly parallel
  A. Create a job in Data Science Jobs and then start the number of simultaneous job runs required for your workload