Explore cloud directions, MLOps, and production data science in this 43-minute video featuring Joseph M. Hellerstein, Professor of Computer Science at UC Berkeley. Delve into key topics including model development, training pipelines, inference, and the importance of data in the ML lifecycle. Examine three critical challenges in MLOps and gain insights into cloud programming and serverless computing. Learn about the RISE of Aqueduct and its impact on tech transfer. Discover practical takeaways for implementing MLOps best practices and leveraging cloud-based solutions to scale data science models while ensuring reliability, maintainability, and scalability in your organization.