Deploy ML Models with FastAPI & Docker
Take your machine learning expertise to the next level with this practical Udemy course on deploying ML models in production. Learn to build scalable, reliable APIs using FastAPI and Docker, ensuring seamless integration into real-world applications. Whether you’re a data scientist or developer, this course bridges the gap between model training and deployment.
Key topics covered:
- Set up FastAPI for creating high-performance ML APIs
- Containerize models using Docker for consistency across environments
- Implement authentication, logging, and error handling
- Deploy to cloud platforms like AWS or Azure
- Optimize performance and automate CI/CD pipelines
Why choose this Udemy course? Gain hands-on experience through real-world projects, including deploying a sentiment analysis model or image classifier. Access downloadable code templates, quizzes, and a Udemy coupon code for limited-time discounts. Beginners get a gradual learning curve, while seasoned practitioners refine deployment strategies.
- Free Udemy course resources: Join live Q&A sessions and community forums
- Lifetime access to updates and best practices
- Certificate of completion to showcase your skills
Enroll now to master production-grade ML deployment—no prior FastAPI or Docker experience required. This Udemy course offers unbeatable value, combining theory with actionable steps for immediate implementation. Don’t miss the free Udemy course coupon included for early sign-ups!
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