Machine Learning in Production
Completed by David Eugen Petcu
May 30, 2026
11 hours (approximately)
David Eugen Petcu'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: Machine Learning
- Category: Data Validation
- Category: Model Optimization
- Category: System Monitoring
- Category: Data Quality
- Category: Continuous Monitoring
- Category: Data Integrity
- Category: Model Training
- Category: Application Deployment
- Category: Data Maintenance
- Category: Unstructured Data
- Category: Model Deployment
