Master Docker for MLOps: From Containers to Production AI APIs

A comprehensive masterclass detailing the implementation of Docker and Machine Learning Operations (MLOps) principles, aiming to streamline the transition from local development environments to production deployment of AI services. The content is structured across five modules, covering fundamental concepts such as Docker installation, image management, and container lifecycles. Subsequent sections focus on practical engineering tasks, including containerizing Flask web applications and utilizing Docker Compose for multi-container setups involving services like MySQL.

The tutorial further addresses professional debugging techniques within running containers and concludes with a dedicated module on packaging trained machine learning models into scalable, production-ready prediction APIs. This instructional resource is designed for software engineers, data scientists, and MLOps professionals seeking to implement containerization for scalable AI workflows and resolve environment inconsistencies.