AI0-001 AI Implementation and Operations Practice Question
Which THREE components are essential in an MLOps pipeline?
⚠ Common exam trap
CompTIA often tests the distinction between operational pipeline components (automation, testing, versioning) and peripheral activities (procurement, manual reviews) to see if candidates understand that MLOps is about automating the ML lifecycle, not general IT operations.
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
✓
Data versioning
Data versioning (A) is essential in an MLOps pipeline because it ensures reproducibility and traceability of datasets used for training, validation, and testing. Without versioning, changes to data cannot be tracked, leading to inconsistent model behavior and difficulty in debugging. Tools like DVC or Git LFS enable precise snapshotting of data, which is critical for auditing and rollback in production AI systems.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Data versioning
Why this is correct
Versioning data is crucial for reproducibility and tracking.
- ✗
Manual code review
Why it's wrong here
While beneficial, manual code review is not a defining component of an automated MLOps pipeline.
- ✓
Deployment automation
Why this is correct
Automation of deployment is key to reliable and frequent releases.
- ✗
Hardware procurement
Why it's wrong here
Procurement is an operational activity, not a pipeline component.
- ✓
Automated model testing
Why this is correct
Automated tests ensure model quality before deployment.
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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.