Level: Beginner to Intermediate

Prerequisite: None

Deanne Larson, Ph.D., DM, CBIP

President

Larson & Associates and TDWI Fellow

Machine learning operations (MLOps) is a process-focused and automated methodology for delivering advanced analytics. Building on the data management foundations of DataOps, MLOps provides end-to-end processes to develop, build, test, and automate machine learning and AI models. MLOps is an emerging practice that organizations want to adopt to decrease model time to market and create reproducible capabilities. This course addresses what MLOps is and how it differs from conventional software development, covers MLOps best practices, and prepares you to get started.

You Will Learn

• The definition and scope of MLOps
• Agile principles that are applied to MLOps projects
• How machine learning models and training sets are incorporated into the CI/CD process
• How MLOps reduces technical debt
• Why MLOps focuses on the automation of the machine learning process
• Best practices and how to get started with MLOps

Geared To

• Project managers
• Data scientists
• Data engineers
• Analysts
• Analytics managers