Machine Learning in Production
Completed by Muhammad Ibrahim Farrukh
January 19, 2026
11 hours (approximately)
Muhammad Ibrahim Farrukh'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 Integrity
- Category: Unstructured Data
- Category: MLOps (Machine Learning Operations)
- Category: Data Maintenance
- Category: Continuous Deployment
- Category: Application Deployment
- Category: Data Quality
- Category: Data Synthesis
- Category: Continuous Monitoring
- Category: Model Training
- Category: Applied Machine Learning
- Category: System Monitoring
