Machine Learning in Production
Completed by IOANNIS BANOUSIS
October 9, 2025
11 hours (approximately)
IOANNIS BANOUSIS'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: Model Evaluation
- Category: Application Deployment
- Category: Applied Machine Learning
- Category: System Monitoring
- Category: Data Synthesis
- Category: MLOps (Machine Learning Operations)
- Category: Data Integrity
- Category: Model Deployment
- Category: Continuous Monitoring
- Category: Unstructured Data
- Category: Data Collection
- Category: Model Training
