Machine Learning in Production
Completed by Francesco Pasanisi
July 25, 2026
11 hours (approximately)
Francesco Pasanisi's account is verified. Coursera certifies their successful completion of Machine Learning in Production
What you will learn
Identify key components of the ML project lifecycle, pipeline & select the best deployment & monitoring patterns for different production scenarios.
Optimize model performance and metrics by prioritizing disproportionately important examples that represent key slices of a dataset.
Solve production challenges regarding structured, unstructured, small, and big data, how label consistency is essential, and how you can improve it.
Skills you will gain
- Category: MLOps (Machine Learning Operations)
- Category: Machine Learning
- Category: Model Optimization
- Category: System Monitoring
- Category: Continuous Monitoring
- Category: Model Training
- Category: Model Deployment
- Category: Data Quality
- Category: Data Integrity
- Category: Unstructured Data
- Category: Application Deployment
- Category: Data Maintenance
