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AIF-C01 practice question: ML lifecycle, MLOps and metrics (3 of 3)

Fundamentals of AI and ML A free question from our original AIF-C01 practice exam. Try it, then open the answer to see why each option is right or wrong.

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A logistics firm's data scientists retrain pricing models by hand on their laptops and copy the files to production when they remember. The CTO wants to adopt MLOps.

Which TWO practices are part of MLOps? (Choose two.)

Choose two answers.

  1. A. Track which data, code and parameters produced each model, so results can be reproduced.
  2. B. Run training, evaluation and deployment through one automated, repeatable pipeline.
  3. C. Freeze each model at release and stop monitoring its predictions in production.
  4. D. Let each scientist release models by hand, using a personal copy of the process.
  5. E. Skip automated tests so that new models reach production faster.
Show the answer and explanation

Answers: A, B

  • A. Right: Correct. Versioning the data, code and model artifacts lets the team reproduce any model and audit how it was made. This is one of the core MLOps practices. Learn more: What is MLOps? (opens in a new tab)
  • B. Right: Correct. Automating each stage in a pipeline makes training and release repeatable and consistent. It replaces manual copying and remembered steps.
  • C. Wrong: MLOps includes continuous monitoring of data and model performance after release. Stopping monitoring removes a key safeguard.
  • D. Wrong: Personal manual processes are the problem the CTO wants to fix. They make releases inconsistent and hard to audit.
  • E. Wrong: MLOps relies on automated testing before release to catch errors. Skipping tests trades a short delay for production failures.

Explanation

MLOps applies DevOps discipline to machine learning, so models are versioned, reproducible and released through automated pipelines. Monitoring and testing also belong to the practice, which is why options that stop them are wrong. This question tests recognizing the core MLOps practices.

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