Machine Learning in Production
Completed by Alexander Bakharev
April 4, 2026
11 hours (approximately)
Alexander Bakharev'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: Data Validation
- Category: Model Optimization
- Category: System Monitoring
- Category: Machine Learning
- Category: Application Deployment
- Category: Data Quality
- Category: Model Training
- Category: Data Synthesis
- Category: Applied Machine Learning
- Category: Continuous Deployment
- Category: Data Maintenance
- Category: MLOps (Machine Learning Operations)
