Machine Learning in Production
Completed by TAHINA PRINCY RANAIVOMANANA
February 27, 2026
11 hours (approximately)
TAHINA PRINCY RANAIVOMANANA'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: Cloud Deployment
- Category: Model Evaluation
- Category: Applied Machine Learning
- Category: Debugging
- Category: Continuous Monitoring
- Category: Machine Learning
- Category: Data Pipelines
- Category: Continuous Deployment
- Category: Data Preprocessing
- Category: Model Deployment
- Category: Feature Engineering
