AI Production Tools and Frameworks

AI production requires more than model development—it requires understanding deployment frameworks, orchestration tools, and performance optimization techniques. This course introduces essential frameworks and tools for deploying AI models to production with a focus on maintainability, scalability, and reliability.

Participants will gain hands-on experience with frameworks like TensorFlow Serving, MLflow, Docker, and Kubernetes, and learn to manage models from training to deployment in production-like environments.

• Use AI deployment frameworks and tools for production.
• Implement scalable model serving strategies.
• Monitor and maintain models in production environments.
• Optimize code and pipelines for performance and reliability.
• Understand the full AI deployment lifecycle.