Machine Learning in Production
Completed by Dipayan Biswas
January 7, 2026
11 hours (approximately)
Dipayan Biswas'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 Maintenance
- Category: Unstructured Data
- Category: Data Collection
- Category: Continuous Deployment
- Category: Data Preprocessing
- Category: System Monitoring
- Category: Application Deployment
- Category: Model Optimization
- Category: Data Validation
- Category: Continuous Monitoring
- Category: MLOps (Machine Learning Operations)
- Category: Data Quality
