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The Oracle 1z0-1110-22 exam covers a wide range of topics, including machine learning algorithms, data visualization, data exploration, data cleansing, data integration, and data transformation. 1z0-1110-22 exam also covers big data technologies such as Apache Hadoop, Apache Spark, and Apache Hive, as well as cloud-based data storage technologies such as Oracle Autonomous Data Warehouse and Oracle Cloud Object Storage.
NEW QUESTION # 18
As you are working in your notebook session, you find that your notebook session does not have enough compute CPU and memory for your workload. How would you scale up your notebook session without losing your work?
- A. Deactivate your notebook session, provision a new notebook session on larger compute shape, and re-create all your file changes.
- B. Create a temporary bucket in Object Storage, write all your files and data to Object Storage, delete tur ctebook session, provision a new notebook session on a larger com-pute shape, and capy your flies and data from your temporary bucket onto your new notebook session.
- C. Down your files and data to your local machine, delete your notebook session, provision tebook session on a larger compute shape, and upload your files from your local the new notebook session.
- D. Ensure your files and environments are written to the block volume storage under the /home/datascience directory, deactivate the notebook session, and activate the notebook larger compute shape selected.
Answer: D
NEW QUESTION # 19
You are using Oracle Cloud Infrastructure Anomaly Detection to train a model to detect anomalies in pump sensor dat a. How does the required False Alarm Probability settings affect an anomaly detection model?
- A. It changes the sensitivity of the model to detect anomalies.
- B. It determines how many false alarms occur before an error message is generated.
- C. It is used to disable the reporting of false alarm.
- D. It Adds a score to each signal indicating the probability that it is false alarm.
Answer: A
NEW QUESTION # 20
What preparation steps are required to access an Oracle AI service SDK from a Data Science notebook session?
- A. Import the REST API
- B. Call the Accented Data Science (ADS) command to enable Al integration
- C. Create and upload execute.py and runtime.yaml
- D. Create and upload the API signing key and config file
Answer: D
NEW QUESTION # 21
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?
- A. Reduce the load balancer bandwidth limit so that fewer requests come in.
- B. Update the deployment to use fewer instances.
- C. Delete the deployment.
- D. Update the deployment to use a larger virtual machine (mare CPUs/memory).
- E. Update the deployment to add more instances.
Answer: E
NEW QUESTION # 22
As a data scientist, you are working on a global health data set that has data from more than 50 countries. You want to encode three features, such as 'countries', 'race', and 'body organ' as categories. Which option would you use to encode the categorical feature?
- A. auto_transform()
- B. DataFramLabelEncode()
- C. OneHotEncoder()
- D. show_in_notebook()
Answer: B
NEW QUESTION # 23
You are preparing a configuration object necessary to create a Data Flow application. Which THREE parameter values should you provide?
- A. The display name of the application.
- B. The bucket used to read/write the pySpark script in Object Storage.
- C. The local path to your pySpark script.
- D. The path to the arhive.zip file.
- E. The compartment of the Data Flow application.
Answer: A,B,C
NEW QUESTION # 24
You want to evaluate the relationship between feature values and model predictions. You sus-pect that some of the features are correlated. Which model explanation technique would you recommend?
- A. Feature Dependence Explanations.
- B. Local Interpretable Model-Agnostic Explanations.
- C. Feature Permutation Importance Explanations.
- D. Accumulated Local Effects.
Answer: B
NEW QUESTION # 25
Using Oracle AutoML, you are tuning hyperparameters on a supported model class and have specified a time budget. AutoML terminates computation once the time budget is exhausted. What would you expect AutoML to return in case the time budget is exhausted before hy-perparameter tuning is completed?
- A. A hyperparameter configuration with a minimum learning rate is returned.
- B. The current best-known hyperparameter configuration is returned.
- C. The last generated hyperparameter configuration is returned.
- D. A random hyperparameter configuration is returned.
Answer: B
NEW QUESTION # 26
You want to ensure that all stdout and stderr from your code are automatically collected and logged, without implementing additional logging in your code. How would you achieve this with Data Science Jobs?
- A. Data Science Jots does not support automatic fog collection and storing.
- B. On job creation, enable logging and select a log group. Then, select either log or the op-tion to enable automatic log creation.
- C. Make sure that your code is using the standard logging library and then store all the logs to Check Storage at the end of the job.
- D. You can implement custom logging in your code by using the Data Science Jobs logging.
Answer: D
NEW QUESTION # 27
For your next data science project, you need access to public geospatial images. Which Oracle Cloud service provides free access to those images?
- A. Oracle Open Data
- B. Oracle Analytics Claud
- C. Oracle Big Data Service
- D. Oracle Cloud Infrastructure (OCI) Data Science
Answer: A
NEW QUESTION # 28
You have received machine learning model training code, without clear information about the optimal shape to run the training on. How would you proceed to identify the optimal compute shape for your model training that provides a balanced cost and processing time?
- A. Start with a random compute shape and monitor the utilization metrics and time required to finish the model training Perform model training optimizations and performance tests in advance to identify the right compute shape before running the model training as a job.
- B. Start with a smaller shape and monitor the utilization metrics and time required to complete the model training. If the compute shape is fully utilized, change to compute that has more resources and re-run the job. Repeat the process until the processing time does not improve.
- C. Start with a smaller shape and monitor the Job Run metrics and time required to complete the model training: If the compute shape is not fully utilized, tune the model parameters, and rerun the job. Repeat the process until the shape resources are fully utilized.
- D. Start with the strangest compute shape Jobs support and monitor the Job Run metrics and time required to complete the model training. Tune the model so that it utilizes as much compute resources as possible, even at an increased cost.
Answer: B
NEW QUESTION # 29
You are a data scientist using Oracle AutoML to produce a model and you are evaluating the score metric for the model. Which of the following TWO prevailing metrics would you use for evaluating multiclass classification model?
- A. F1 Score
- B. Recall
- C. R-Squared
- D. Explained variance score
- E. Mean squared error
Answer: A,B
NEW QUESTION # 30
You are asked to prepare data for a custom-built model that requires transcribing Spanish video recordings into a readable text format with profane words identified. Which Oracle Cloud service would you use?
- A. OCI Language
- B. OCI Anomaly Detection
- C. OCI Translation
- D. OCI Speech
Answer: D
NEW QUESTION # 31
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. ADSTuner
- B. EvaluationMetrics
- C. ADS Explainer
- D. ADS Evaluator
Answer: B
NEW QUESTION # 32
You are a data scientist leveraging Oracle Cloud Infrastructure (OCI) Data Science to create a model and need some additional python libraries for processing genome sequencing dat a. Which of the following THREE statements are correct with respect to installing additional Python libraries to process the data?
- A. OCI Data Science allows privileges in notebook sessions.
- B. You can install private or custom libraries from your own internal repositories
- C. You cannot install a library that's not preinstalled in the provided image
- D. You can install any open source package available in a publicly accessible Python Package Index (PyPI) repository
- E. You can only install libraries using yum and pip as a normal user
Answer: B,D,E
NEW QUESTION # 33
You want to make your model more parsimonious to reduce the cost of collecting and processing dat a. You plan to do this by removing features that are highly correlated. You would like to create a heat map that displays the correlation so that you can identify candidate features to remove. Which Accelerated Data Science (ADS) SDK method would be appropriate to display the correlation between Continuous and Categorical features?
- A. Cramersv_plot{}
- B. Correlation_ratio_plot{}
- C. Pearson_plot{}
- D. Corr{}
Answer: B
NEW QUESTION # 34
You are a computer vision engineer building an image recognition model. You decide to use Oracle Data Labeling to annotate your image dat a. Which of the following THREE are possible ways to annotate an image in Data Labeling?
- A. Adding labels to an image by drawing bounding box to an image, is not supported by Data Labeling
- B. Adding labels to an image using object detection, by drawing bounding boxes to an im-age.
- C. Adding multiple labels to an image.
- D. Adding a single label to an image.
- E. Adding labels to image using semantic segmentation, by drawing multiple bounding boxes to an image.
Answer: B,C,D
NEW QUESTION # 35
As a data scientist, you are tasked with creating a model training job that is expected to take different hyperparameter values on every run. What is the most efficient way to set those pa-rameters with Oracle Data Science Jobs?
- A. Create a new job every time you need to run your code and pass the parameters as en-vironment variables.
- B. Create a new no by setting the required parameters in your code, and create a new job for mery code change.
- C. Create your code to expect different parameters either as environment variables or as command line arguments, which are set on every job run with different values.
- D. Create your code to expect different parameters as command line arguments, and create it new job every time you run the code.
Answer: C
NEW QUESTION # 36
You trained a model to predict housing prices for your city. Which two metrics from the Ac-celerated Data Science (ADS) Evaluation class can be used to evaluate the regression model you just trained?
- A. Weighted Precision
- B. Mean Absolute Error
- C. Weighted Recall
- D. Explained Variance Score
- E. F-1 Score
Answer: B,D
NEW QUESTION # 37
Which of the following TWO non-open source JupyterLab extensions has Oracle Cloud In-frastructure (OCI) Data Science developed and added to the notebook session experience?
- A. Command Palette
- B. Environment Explorer
- C. Table of Contents
- D. Terminal
- E. Notebook Examples
Answer: B,E
NEW QUESTION # 38
You are a data scientist with a set of text and image files that need annotation, and you want to use Oracle Cloud Infrastructure (OCI) Data Labeling. Which of the following THREE an-notation classes are supported by the tool.?
- A. Semantic Segmentation
- B. Object Detection
- C. Key-Point and Landmark
- D. Named Entity Extraction
- E. Classification (single/multi label)
- F. Polygonal Segmentation
Answer: B,D,E
NEW QUESTION # 39
The feature type TechJob has the following registered validators: Tech-Job.validator.register(name='is_tech_job', handler=is_tech_job_default_handler) Tech-Job.validator.register(name='is_tech_job', handler= is_tech_job_open_handler, condi-tion=('job_family',)) TechJob.validator.register(name='is_tech_job', handler= is_tech_job_closed_handler, condition=('job_family': 'IT')) When you run is_tech_job(job_family='Engineering'), what does the feature type validator system do?
- A. Throw an error because the system cannot determine which handler to run.
- B. Execute the is_tech_job_open_handler handler.
- C. Execute the is_tech_job_closed_handler handler.
- D. Execute the is_tech_job_default_handler sales handler.
Answer: A
NEW QUESTION # 40
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Oracle Cloud Infrastructure Data Science 2022 Professional certification exam is designed to test the skills and knowledge of professionals working in the field of data science. 1z0-1110-22 exam covers a range of topics related to data preparation, model development, and deployment, as well as advanced topics such as model performance optimization and security. Professionals who earn the certification gain increased credibility and recognition in the field of data science, as well as better job opportunities and higher salaries. To prepare for the exam, professionals should have a strong background in data science and machine learning and should take advantage of a range of study materials.
To earn the Oracle Cloud Infrastructure Data Science 2022 Professional certification, candidates must successfully pass the 1z0-1110-22 certification exam. 1z0-1110-22 exam comprises 60 multiple-choice questions and has a time limit of 90 minutes. 1z0-1110-22 exam is available in English only, and the passing score is 65%.
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