FieldsMLOps Engineer
MLOps Engineer
Take machine-learning models from notebook to dependable production.
Career pathMonths of workCapability pathWeeks of work
What Safua will teach
What you learn as a MLOps Engineer
- Packaging and serving models reliably
- Building training and deployment pipelines
- Monitoring models for drift and degradation
- Versioning data, models, and experiments
Example concepts
What you will understand
- Model packaging and serving
- Feature stores and reproducible pipelines
- Monitoring, drift, and retraining
- Experiment and model versioning
Example practice
How you will practice
- Serve a trained model behind a tested endpoint
- Add monitoring that would catch model drift
- Make a training run fully reproducible
Example projects
What you will build
- A serving pipeline with monitoring and a rollback path
- A reproducible training pipeline with versioned artifacts
The proof you build
What a credential here means
Evidence that you can operationalize a model with serving, monitoring, versioning, and a safe path to update it.
Your work is observed with your consent, scored for independence and assistance, and turned into proof that carries a confidence level. The career path can reach a high-assurance credential, anchored by a scored capstone.
Start with MLOps Engineer
Join the early-access list for MLOps Engineer. We will let you know when preview access opens.
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