Machine Learning in Production
Completed by Henry Plaskonos
May 16, 2025
11 hours (approximately)
Henry Plaskonos'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: MLOps (Machine Learning Operations)
- Category: Continuous Monitoring
- Category: Continuous Deployment
- Category: Application Deployment
- Category: Model Evaluation
- Category: Model Training
- Category: Model Deployment
- Category: Data Collection
- Category: Data Validation
- Category: Data Preprocessing
- Category: Applied Machine Learning
