Machine Learning in Production
Completed by SAKASH SRIVASTAVA
March 6, 2026
11 hours (approximately)
SAKASH SRIVASTAVA'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 Optimization
- Category: Application Deployment
- Category: System Monitoring
- Category: Machine Learning
- Category: Continuous Monitoring
- Category: Model Deployment
- Category: Model Evaluation
- Category: Data Maintenance
- Category: Continuous Deployment
- Category: MLOps (Machine Learning Operations)
- Category: Data Preprocessing
- Category: Data Integrity
