A professional-level course focused on how to design, build, deploy, and maintain machine learning systems in real production environments. It goes beyond model training and emphasizes the full ML ifecycle, including data pipelines, monitoring, deployment strategies, and handling real-world issues such as drift, data quality, and system constraints.The course teaches how to move from experimental ML models to robust, continuously operating production systems that deliver reliable AI-driven decisions in practice.