Machine Learning in Production
Completed by Artemiy Solyakov
June 13, 2025
11 hours (approximately)
Artemiy Solyakov'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 Quality
- Category: Continuous Deployment
- Category: Model Deployment
- Category: Debugging
- Category: Machine Learning
- Category: Data Preprocessing
- Category: MLOps (Machine Learning Operations)
- Category: Feature Engineering
- Category: Data Pipelines
- Category: Cloud Deployment
- Category: Model Evaluation
- Category: Continuous Monitoring
