MLOps and LLMOps: Deploying and Scaling AI in Production
Completed by Oleksandra Dombrovska
May 8, 2026
17 hours (approximately)
Oleksandra Dombrovska's account is verified. Coursera certifies their successful completion of MLOps and LLMOps: Deploying and Scaling AI in Production
What you will learn
Configure CI/CD pipelines for ML and LLM systems using GitHub Actions and MLflow
Optimize LLM inference pipelines for reduced latency, token cost, and improved reliability
Build automated evaluation frameworks using LLM-as-a-Judge and quality gates
Instrument production AI systems with tracing, drift detection, and observability dashboards
Skills you will gain
- Category: Event Monitoring
- Category: Model Deployment
- Category: Continuous Monitoring
- Category: Model Training
- Category: Retrieval-Augmented Generation
- Category: LLM Application
- Category: AI Workflows
- Category: Model Evaluation
- Category: Scalability
- Category: AI Security
- Category: MLOps (Machine Learning Operations)
- Category: CI/CD
