After doing these courses, I feel confident creating professional visualizations and dashboards
Shoebur RahmanProcurement Specialist, Giz Bangladesh
Course Description
This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models.
Prerequisites
There are no prerequisites for this course
Curriculum
Course outline
1
Welcome to the Machine Learning Operations (MLOps): Getting Started
2
Employing Machine Learning Operations
This module identifies ML practitioners' pain points before exploring the concept of DevOps in ML. You're introduced to the three phases of the ML lifecycle and automating the ML process.
3
Vertex AI and MLOps on Vertex AI
This module explores what Vertex AI is and why a unified platform matters.
4
Summary
Summary
R
Machine Learning Operations (MLOps): Getting Started
Course
Complete
