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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.


Languages Available: English | 日本語 | Português BR | 한국어

Skill Level
Associate
Duration
4h
Prerequisites

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

Outline

Modern MLOps
Defining MLOps
MLOps on Databricks
Working with Asset Bundles

Architecting MLOps Solutions

Introduction 
Opinionated MLOps Principles
Recommended MLOps Architectures
Model Testing Job with the Databricks CLI

Implementation and Monitoring MLOps Solution

Introduction 
Implementation of MLOps Stacks
Type of Model Monitoring
Monitoring in Machine Learning
Lakehouse Monitoring Dashboard

Upcoming Public Classes

Date
Time
Language
Price
Jan 27
01 PM - 05 PM (Europe/London)
English
$750.00
Jan 28
08 AM - 12 PM (America/New_York)
English
$750.00
Jan 30
01 PM - 05 PM (Asia/Kolkata)
English
$750.00
Mar 27
09 AM - 01 PM (Asia/Kolkata)
English
$750.00
Mar 27
01 PM - 05 PM (America/New_York)
English
$750.00
Mar 28
09 AM - 01 PM (Europe/London)
English
$750.00

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