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Oracle Cloud Infrastructure Data Science Professional Sample Questions:

1. You are working as a Data Scientist for a healthcare company. You have a series of neurophysiological data on OCI Data Science and have developed a convolutional neural network (CNN) classification model. It predicts the source of seizures in drug-resistant epileptic patients. You created a model artifact with all the necessary files. When you deployed the model, it failed to run because you did not point to the correct conda environment in the model artifact. Where would you provide instructions to use the correct conda environment?

A) requirements.txt
B) runtime.yaml
C) score.py
D) model_artifact_validate.py

2. As a data scientist, you are working on a global health dataset 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) DataFrameLabelEncode()
B) show_in_notebook()
C) OneHotEncoder()
D) auto_transform()

3. 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 provenance details
D) Check for metadata tags

4. 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 annotation classes are supported by the tool?

A) Classification (single/multi-label)
B) Key-point and landmark
C) Named entity extraction
D) Polygonal segmentation
E) Semantic segmentation
F) Object detection

5. 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 parameters with Oracle Data Science Jobs?

A) Create a new job every time you need to run your code and pass the parameters as environment variables
B) Create your code to expect different parameters as command-line arguments and create a new job every time you run the code
C) Create a new job by setting the required parameters in your code and create a new job for every code change
D) 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

Solutions: