• Online, Self-Paced
Course Description

ML pipelines help organizations improve the standards of machine learning (ML) models, improve their business strategy, and reduce redundant work and miscommunication. They consist of a series of ML workflow steps performed in a connected and automated/semi-automated way. Through this course, learn the basics of ML pipelines.

Discover the uses and benefits of ML pipelines and the characteristics of manual and automated pipelines. Next, explore best practices for building pipelines and the three types of environments in the MLOps process. Finally, examine the importance of CI/CD in ML, the purpose of ML pipeline testing, and ML pipeline testing tools and frameworks.

Upon completion, you'll be able to define ML pipelines and their benefits.

Learning Objectives

{"discover the key concepts covered in this course"}

Framework Connections

The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):

Specialty Areas

  • Systems Architecture
  • Systems Development