MLOps & LLMOps Practice Tests: 180 Questions

180 questions with detailed explanations to test your MLOps skills for the 2026/27 landscape.

This course gives you 6 practice tests, 30 questions each, across the topics that matter for MLOps and LLMOps work right now:

1. MLOps Fundamentals (lifecycle, roles, reproducibility, team setup)

2. CI/CD for ML (testing strategy, pipelines, release gates, rollback)

3. Monitoring, Logging and Drift Detection (data drift, concept drift, alerting, observability)

4. Model Deployment and Serving (batch, online, streaming, edge, canary/shadow/blue-green)

5. Experiment Tracking and Data Versioning (MLflow and DVC, reproducibility, lineage)

6. LLMOps (prompts, RAG, vector stores, evaluation, guardrails, prompt injection, agents)

Every question includes a written explanation. If you get one wrong you walk away understanding why, not just which letter was right. You can use the explanation as a starting point for deeper study.

Here's a sample:

Q:

What dvc command updates already-tracked changed files before pushing?

A:

dvc commit

Explanation:

After changes to a file already tracked by DVC (added previously with dvc add), running "dvc commit" updates that file in the local cache before pushing the changes to remote storage with dvc push.

How good are you at:

• Designing CI/CD pipelines for ML model deployment?

• Catching data and concept drift before it reaches production users?

• Tracking experiments and versioning datasets with MLflow and DVC?

• Choosing between online, batch, streaming, and edge serving patterns?

• Running a RAG pipeline and keeping an LLM application evaluable and safe?

Take the practice tests and get an objective read on your skillset.

The course is actively maintained, and student feedback shapes what gets added next.