Machine Learning in Production
Completed by Nikita Markovnikov
July 6, 2025
11 hours (approximately)
Nikita Markovnikov'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 Preprocessing
- Category: Application Deployment
- Category: Continuous Deployment
- Category: MLOps (Machine Learning Operations)
- Category: Data Maintenance
- Category: Model Deployment
- Category: Data Validation
- Category: Continuous Monitoring
- Category: Model Evaluation
- Category: Data Collection
- Category: Applied Machine Learning
- Category: Data Synthesis
