AI0-001 AI Implementation and Operations Practice Question
Exhibit
Refer to the exhibit.
```
{
"pipeline_version": "2.1",
"components": {
"data_ingestion": {
"source": "s3://data-bucket/transactions/",
"schedule": "cron(0 2 * * ? *)"
},
"feature_engineering": {
"script": "features.py",
"parameters": {
"window_size": 7,
"aggregation": "mean"
}
},
"model_training": {
"algorithm": "xgboost",
"hyperparameters": {
"n_estimators": 100,
"learning_rate": 0.1
},
"training_data_version": "v1"
},
"model_evaluation": {
"metrics": ["accuracy", "precision", "recall"],
"threshold": {"accuracy": 0.85, "precision": 0.80}
},
"model_deployment": {
"target": "production",
"rollback_condition": "if_accuracy_drops_below_0.85"
}
}
}
```Refer to the exhibit. A machine learning pipeline configuration is shown. During a deployment, the model evaluation passes with accuracy 0.86 and precision 0.79. However, the pipeline proceeds to deploy. What is the most likely reason for this behavior?
⚠ Common exam trap
CompTIA often tests the misconception that all evaluation metrics automatically trigger rollback conditions, when in fact only metrics explicitly listed in the condition logic are checked.
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
✓
The deployment only checks the accuracy threshold for rollback condition
The pipeline configuration shows a rollback condition that only checks the accuracy metric (accuracy < 0.85). Since the model achieved accuracy 0.86, which is above the threshold, the condition is not triggered, and the pipeline proceeds to deploy regardless of the precision value. The precision metric is not part of the rollback evaluation logic in this configuration.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The precision metric is not included in the evaluation script
Why it's wrong here
Precision is listed in metrics, so it is computed.
- ✓
The deployment only checks the accuracy threshold for rollback condition
Why this is correct
The rollback_condition only mentions accuracy, so precision threshold is ignored.
- ✗
The deployment target is set to staging instead of production
Why it's wrong here
The target is 'production', so that's not the issue.
- ✗
The operator manually overrode the threshold
Why it's wrong here
No evidence of manual intervention in the exhibit.
About these practice questions
Courseiva writes every AI0-001 question from scratch — 754 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI0-001 practice question is part of Courseiva's free CompTIA 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 AI0-001 exam.