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Oracle Cloud Infrastructure Data Science Professional Sample Questions:

1. True or false? Data scientists typically need a combination of technical skills, nontechnical ones, and suitable personality traits to be successful.

A) False
B) True

2. When preparing your model artifact to save it to the Oracle Cloud Infrastructure (OCI) DataScience model catalog, you create a score.py file. What is the purpose of the score.py file?

A) Define the inference server dependencies
B) Configure the deployment infrastructure
C) Execute the inference logic code
D) Define the compute scaling strategy

3. How can you collaborate with team members in OCI Data Science Workspace?

A) By using version control systems integrated with the workspace
B) By sharing the workspace instance with other users
C) By granting access to specific notebooks and files
D) By enabling chat and video conferencing within the workspace

4. Which CLI command allows the customized conda environment to be shared with co-workers?

A) odsc conda clone
B) odsc conda install
C) odsc conda modify
D) odsc conda publish

5. You have a complex Python code project that could benefit from using Data Science Jobs as it is a repeatable machine learning model training task. The project contains many sub-folders and classes. What is the best way to run this project as a Job?

A) ZIP the entire code project folder, upload it as a Job artifact on job creation, and set JOB_RUN_ENTRYPOINT to point to the main executable file
B) Rewrite your code so that it is a single executable Python or Bash/Shell script file
C) ZIP the entire code project folder and upload it as a Job artifact on job creation. Jobs identifies the main executable file automatically
D) ZIP the entire code project folder and upload it as a Job artifact. Jobs automatically identifies the main top-level where the code is run

Solutions: