Machine Learning Operations
This course will guide participants through a comprehensive exploration of machine learning model operations, focusing on MLOps and model lifecycle management. The initial segment covers essential MLOps components and best practices, providing participants with a strong foundation for effectively operationalizing machine learning models. In the latter part of the course, we will delve into the basics of the model lifecycle, demonstrating how to navigate it seamlessly using the Model Registry in conjunction with the Unity Catalog for efficient model management. By the course's conclusion, participants will have gained practical insights and a well-rounded understanding of MLOps principles, equipped with the skills needed to navigate the intricate landscape of machine learning model operations.
Note: This is the fourth course in the 'Machine Learning with Databricks’ series.
At a minimum, you should be familiar with the following before attempting to take this content:
Knowledge of fundamental concepts of machine learning
Knowledge of MLflow tracking
Familiarity with Databricks workspace and notebooks
Intermediate level knowledge of Python
Self-Paced
Custom-fit learning paths for data, analytics, and AI roles and career paths through on-demand videos
Registration options
Databricks has a delivery method for wherever you are on your learning journey
Self-Paced
Custom-fit learning paths for data, analytics, and AI roles and career paths through on-demand videos
Register now
Instructor-Led
Public and private courses taught by expert instructors across half-day to two-day courses
Register now
Blended Learning
Self-paced and weekly instructor-led sessions for every style of learner to optimize course completion and knowledge retention. Go to Subscriptions Catalog tab to purchase
Purchase now
Skills@Scale
Comprehensive training offering for large scale customers that includes learning elements for every style of learning. Inquire with your account executive for details
