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Oracle 1Z0-1110-26 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| MLOps and OCI Integration | 20% | - Automation and pipelines
|
| Model Development and Deployment | 30% | - Model deployment
|
| Machine Learning Fundamentals | 20% | - Supervised learning
|
| OCI Data Science Service | 30% | - Projects and notebooks
|
Oracle Cloud Infrastructure Data Science Professional Sample Questions:
1. You are given a task of writing a program that sorts document images by language. Which Oracle AI Service would you use?
A) OCI Language
B) OCI Vision
C) Oracle Digital Assistant
D) OCI Speech
2. What happens when a notebook session is deactivated?
A) The data on boot volume is preserved
B) Compute cost increases due to frequent deactivation
C) The underlying compute instance stops
D) The block volume attached to the notebook is permanently deleted
3. 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 and upload it as a Job artifact on job creation. Jobs identifies the main executable file automatically
B) Rewrite your code so that it is a single executable Python or Bash/Shell script file
C) 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
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
4. What is a common maxim about data scientists?
A) They spend 80% of their time on failed analytics projects and 20% doing useful work.
B) They spend 80% of their time analyzing data and 20% finding and preparing it.
C) They spend 80% of their time finding and preparing data and 20% analyzing it.
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:
| Question # 1 Answer: A | Question # 2 Answer: C | Question # 3 Answer: C | Question # 4 Answer: C | Question # 5 Answer: D |
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