This course provides an in-depth exploration of the intersection of cloud computing and machine learning (ML). Students will gain theoretical and practical knowledge of deploying, scaling, and managing ML models on cloud platforms. The course focuses on leveraging cloud-native tools, infrastructure, and best practices to design efficient, scalable, and cost-effective ML workflows. Key topics include cloud-based ML frameworks, data preprocessing, feature engineering, model training and evaluation, automated model deployment, model optimization, and monitoring in cloud-based machine learning systems.