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Microsoft DW-202 - Azure Machine Learning and MLOps

Length 4 day

Course overview

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Why study this course

This course provides an in-depth exploration of Azure Machine Learning (Azure ML) and its comprehensive tools for automating, training, deploying, and managing machine learning models. Students will gain hands-on experience with Azure’s powerful ML tools, building pipelines, and operationalising machine learning workflows using MLOps principles. Additionally, the course includes modules on security, governance, and the responsible use of AI, which are essential for modern AI development.

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What you’ll learn

After completing this course, students will be able to:

Automate and deploy Azure Machine Learning models
Using Generative AI in Azure Machine Learning
Operationalise with MLOps

Microsoft Azure at Lumify Work

Lumify Work has been delivering effective training across all Microsoft products for over 30 years. We are proud to be both Australia's and New Zealand’s first Microsoft Gold Learning Solutions Partner and the winner of the Microsoft MCT Superstars Award for FY24, which formally recognises us as having the highest quality Microsoft Certified Trainers (MCTs) in ANZ. All Lumify Work Microsoft Azure courses follow Microsoft Official Curriculum (MOC) and are led by MCTs.

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Who is the course for?

Data Scientists
IT Professionals
Developers
DevOps Engineers
Business Analysts
Data Analysts

Course subjects

Module 01: Introduction to Azure Machine Learning

What is machine learning?
What is Azure Machine Learning?
Azure Machine Learning CLI & Python SDK v2
Creating ML resources and getting started with Azure Machine Learning
Working with Data
- Overview of Data concepts in Azure Machine Learning
- Creating datastores
- Creating connections (preview)
- Preparing data with Apache Spark
- Understanding Managed feature store

Hands on labs

Prepare dataset, train and deploy a classification model, using Azure Machine Learning Studio
Create a labeled dataset using Azure Machine Learning data labeling tools
Develop and register a feature set with managed feature store and train models by using features

Module 02: Automating and deploying Azure Machine Learning models

Training models with Azure Machine Learning
Overview of Automated machine learning (AutoML)
Deploying Azure ML models
Monitoring models with Azure Machine Learning
MLflow and Azure Machine Learning

Hands on labs

Train a classification model with no-code AutoML in the Azure Machine Learning studio
Forecast demand with no-code Automated Machine Learning in the Azure Machine Learning studio
Train the best Regression model for the Hardware dataset

Module 03: Using Generative AI in Azure Machine Learning

Working with Azure Machine Learning pipelines and components
Understanding Model Catalog and Collections
Overview of Azure Machine Learning prompt flow
Understanding Retrieval Augmented Generation using Azure Machine Learning prompt flow (preview)
Implementing Vector stores in Azure Machine Learning (preview)
Model monitoring for generative AI applications (preview)

Hands on labs

Develop, test and evaluate prompt flow
End-to-end process for building RAG applications using prompt flow in Azure AI Studio

Module 04: Operationalise with MLOps

Operationalise with MLOps
Introduction to Git integration for Azure Machine Learning
Using Azure Pipelines with Azure Machine Learning
Using GitHub Actions with Azure Machine Learning
GenAIOps (LLMOps) for MLOps practitioners
- Implementing GenAIOps with prompt flow and GitHub
Securing AI Applications on Azure
- Implementing Security and governance for Azure Machine Learning
Responsible use of AI
- Configuring Responsible AI dashboards
- Sharing Responsible AI insights using the Responsible AI scorecard (preview)

Hands on labs

Set up MLOps with GitHub
Implement end-to-end approach for MLOps(v2) in Azure using GitHub Workflows
Implement GenAIOps with prompt flow and GitHub

Prerequisites

Basic knowledge of machine learning concepts
Familiarity with Python programming
Experience with data manipulation and analysis
A basic understanding of cloud computing and Azure services is recommended

Terms & Conditions

The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.