Data Preparation, Feature Engineering, and Augmentation for AI Models

In this advanced course, Dan Sullivan—a cloud architect, author, and Google Cloud expert—delves into data engineering techniques for building AI systems. Learn about data preparation, including, data quality assessment, generating vector representations, encodings and other processes needed to support production AI applications. Explore ways to use ontologies, taxonomies, knowledge graphs and other augmentation techniques to enhance knowledge and reasoning capabilities of AI applications. Deep dive into quality monitoring, with an emphasis on automated validation frameworks and metadata management. Plus, find out how you identify data sources, apply data quality checks, and assess the quality of models for production AI systems.