Machine Learning in Production
Completed by Grace Kimes
January 20, 2026
11 hours (approximately)
Grace Kimes'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 Evaluation
- Category: Model Training
- Category: Applied Machine Learning
- Category: Unstructured Data
- Category: Data Integrity
- Category: Data Synthesis
- Category: Data Preprocessing
- Category: Data Collection
- Category: Machine Learning
- Category: Model Optimization
- Category: System Monitoring
