Introduction to MLOps Theory

4 hours of instruction

This theoretical course gives a comprehensive overview of the topics that make up the emerging trend of MLOps. It is suitable for those who are interested in obtaining a big-picture blueprint of the MLOps space and different types of version control within the ML-driven systems.

OBJECTIVES

1. Describe MLOps and its uses
2. Recognize gaps in the machine learning workflow and identify tools to fix them

PREREQUISITES

Optimizing Ensemble Methods

SYLLABUS & TOPICS COVERED

1. Introduction and benefits of MLOps
   • ‘Define MLOps and summarize its importance’
   • ‘Describe the benefits of MLOps’
2. Version Control In Machine learning
   • ‘Explain the importance of version control in ML’
   • ‘Compare and contrast version control types’
3. Version control in ML process and tools
   • ‘Apply version control to each step in the ML process’
   • ‘Evaluate popular version control tools’
4. Machine learning pipeline structure
   • ‘Describe the ML pipeline’
   • ‘Analyze the importance of CI/CD in ML’

SOFTWARE REQUIREMENTS

TBD