ML Model Deployment: Build a Production API with FastAPI
Completed by Robert Hamilton
September 18, 2026
5 hours (approximately)
Robert Hamilton's account is verified. Coursera certifies their successful completion of ML Model Deployment: Build a Production API with FastAPI
What you will learn
Build production-grade REST APIs for ML model inference using FastAPI with input validation, error handling, and async endpoints
Containerize ML applications with Docker using optimized multi-stage builds, layer caching, and security best practices
Design and implement CI/CD pipelines with GitHub Actions for automated testing, building, and deploying ML services
Skills you will gain
- Category: Model Evaluation
- Category: DevOps
- Category: Continuous Deployment
- Category: Model Deployment
- Category: Application Programming Interface (API)
- Category: Kubernetes
- Category: API Design
- Category: MLOps (Machine Learning Operations)
- Category: API Testing
- Category: Application Deployment
- Category: Applied Machine Learning
- Category: Docker (Software)
