Machine Learning in Production
Completed by Niki Sheibani
August 14, 2025
11 hours (approximately)
Niki Sheibani'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: Continuous Monitoring
- Category: Continuous Deployment
- Category: Model Deployment
- Category: Data Quality
- Category: Model Training
- Category: Data Integrity
- Category: Unstructured Data
- Category: Data Preprocessing
- Category: Model Evaluation
- Category: Data Collection
- Category: Applied Machine Learning
- Category: Data Validation
