Foundational Data Design and AI Development

О курсе

Learn how to design structured datasets and leverage generative AI tools to support data engineering workflows in this foundational course within the Data Engineering Skill Path. You will develop essential competencies including translating business requirements into well-structured tables, applying First Normal Form (1NF) to organize data, performing basic structural transformations using SQL, generating synthetic data for testing, and using AI tools to produce or explain code for pipeline tasks. Through hands-on practice with relational databases, SAS PROC SQL, Microsoft Fabric environments, and generative AI platforms, you will gain the skills needed to design, refine, and augment early-stage data engineering solutions. This course combines expertise from IBM, SAS, Whizlabs, and IBM AI specialists, offering multiple perspectives on data modeling, SQL transformation, Lakehouse-oriented design, and AI-assisted development. You will progress from foundational relational modeling to applying SQL transformations, to structuring Lakehouse data using normalization principles, and finally to using AI tools to enhance productivity and support pipeline development. The curriculum balances conceptual understanding with practical exercises, preparing you to confidently design data structures and incorporate AI into modern data engineering workflows. Perfect for aspiring data engineers and learners seeking foundational skills in data design, modeling, and AI-supported development.

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