Machine Learning in Production
Completed by Dmitry Mironov
September 10, 2025
11 hours (approximately)
Dmitry Mironov'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: Continuous Monitoring
- Category: MLOps (Machine Learning Operations)
- Category: Applied Machine Learning
- Category: Unstructured Data
- Category: Application Deployment
- Category: Data Integrity
- Category: Continuous Deployment
- Category: Data Maintenance
- Category: Data Quality
- Category: Data Collection
- Category: Model Deployment
