- A
HyperparameterTuningJob
Why wrong: HyperparameterTuningJob is for tuning hyperparameters, not a single training job.
- B
CustomJob
Correct: CustomJob (or TrainingJob) is the GCPC component to run a custom training job on Vertex AI.
- C
BatchPredictionJob
Why wrong: BatchPredictionJob is for batch predictions, not training.
- D
ModelDeploy
Why wrong: ModelDeploy is for deploying models to endpoints, not for training.
Question 317 of 1,000
PMLE Automating and Orchestrating ML Pipelines Practice Question
This PMLE practice question tests your understanding of automating and orchestrating ml pipelines. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A machine learning engineer is building a Vertex AI pipeline that uses a pre-built Google Cloud Pipeline Components (GCPC) to train a custom model. Which component should the engineer use to submit a custom training job to Vertex AI?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
CustomJob
The CustomJob component is the correct choice because it is the pre-built GCPC component specifically designed to submit a custom training job to Vertex AI. It allows the engineer to specify a custom container image or a Python training script, along with machine configuration and hyperparameters, directly within a Vertex AI pipeline. Other components serve different purposes, such as hyperparameter tuning, batch predictions, or model deployment.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
HyperparameterTuningJob
Why it's wrong here
HyperparameterTuningJob is for tuning hyperparameters, not a single training job.
- ✓
CustomJob
Why this is correct
Correct: CustomJob (or TrainingJob) is the GCPC component to run a custom training job on Vertex AI.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
BatchPredictionJob
Why it's wrong here
BatchPredictionJob is for batch predictions, not training.
- ✗
ModelDeploy
Why it's wrong here
ModelDeploy is for deploying models to endpoints, not for training.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse HyperparameterTuningJob with CustomJob because both involve training, but HyperparameterTuningJob is for multi-trial optimization, not a single training run, and ModelDeploy is a distractor that does not exist as a GCPC component.
Detailed technical explanation
How to think about this question
Under the hood, the CustomJob component creates a Vertex AI CustomJob resource, which launches a training task on a specified machine type (e.g., n1-standard-4) with optional GPU support and distributed training configurations. A subtle behavior is that the component automatically handles the packaging of the training code into a Docker container if using a Python package, and it integrates with Vertex AI's experiment tracking and artifact lineage. In a real-world scenario, this component is essential when the training code requires custom dependencies or non-standard frameworks not supported by pre-built training containers.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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Automating and Orchestrating ML Pipelines — study guide chapter
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FAQ
Questions learners often ask
What does this PMLE question test?
Automating and Orchestrating ML Pipelines — This question tests Automating and Orchestrating ML Pipelines — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: CustomJob — The CustomJob component is the correct choice because it is the pre-built GCPC component specifically designed to submit a custom training job to Vertex AI. It allows the engineer to specify a custom container image or a Python training script, along with machine configuration and hyperparameters, directly within a Vertex AI pipeline. Other components serve different purposes, such as hyperparameter tuning, batch predictions, or model deployment.
What should I do if I get this PMLE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jul 4, 2026
This PMLE practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PMLE exam.
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