Oracle Cloud Infrastructure 2025 Data Science Professional 1z0-1110-25 Question # 9 Topic 1 Discussion
1z0-1110-25 Exam Topic 1 Question 9 Discussion:
Question #: 9
Topic #: 1
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 a new job by setting the required parameters in your code and create a new job for every 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 a new job every time you run the code
Objective: Efficiently vary hyperparameters in OCI Jobs.
Evaluate Options:
A: New job per run—Wastes setup time.
B: Code changes per job—Inefficient, error-prone.
C: Flexible params per run—Efficient, reusable—correct.
D: New job per run—Redundant effort.
Reasoning: C minimizes job creation, maximizes flexibility.
Conclusion: C is correct.
OCI documentation states: “For varying hyperparameters, configure a single Job with code accepting environment variables or command-line arguments (C), set per run—most efficient.” A and D over-create jobs, B ties params to code—only C optimizes.
Oracle Cloud Infrastructure Data Science Documentation, "Job Parameterization".
Contribute your Thoughts:
Chosen Answer:
This is a voting comment (?). You can switch to a simple comment. It is better to Upvote an existing comment if you don't have anything to add.
Submit