Training: Designing and Implementing a Data Science Solution on Azure

Ref. DP-100T01

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Duration:

4

days

Exam:

Optional

Level:

Intermediate

Funding:

Temptraining

ITTA | Trainings | IT Pro | Analytics and Data Management | Designing and Implementing a Data Science Solution on Azure

Description

In this course you will learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This training teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure.

Participant profiles

Data Specialist

Objectives

Able to use Azure services and develop, train, and deploy, machine learning solutions

Prerequisites

Have followed the course: Microsoft Azure Fundamentals (AZ-900)
Understanding of data science including how to prepare data, train models, and evaluate competing models to select the best one
How to program in the Python programming language and use the Python libraries: pandas, scikit-learn, matplotlib, and seaborn

Course content

Module 1: Design a data ingestion strategy for machine learning projects

Identify your data source and format
Choose how to serve data to machine learning workflows
Design a data ingestion solution

Module 2: Design a machine learning model training solution

Identify machine learning tasks
Choose a service to train a machine learning model
Decide between compute options

Module 3: Design a model deployment solution

Understand how model will be consumed
Decide on real-time or batch deployment

Module 4: Explore Azure Machine Learning workspace resources and assets

Create an Azure Machine Learning workspace
Identify Azure Machine Learning resources
Identify Azure Machine Learning assets
Train models in the workspace

Module 5: Explore developer tools for workspace interaction

Explore the studio
Explore the Python SDK
Explore the CLI

Module 6: Make data available in Azure Machine Learning

Understand URIs
Create a datastore
Create a data asset

Module 7: Work with compute targets in Azure Machine Learning

Choose the appropriate compute target
Create and use a compute instance
Create and use a compute cluster

Module 8: Work with environments in Azure Machine Learning

Understand environments
Explore and use curated environments
Create and use custom environments

Module 9: Find the best classification model with Automated Machine Learning

Preprocess data and configure featurization
Run an Automated Machine Learning experiment
Evaluate and compare models

Module 10: Track model training in Jupyter notebooks with MLflow

Configure MLflow for model tracking in notebooks
Train and track models in notebooks

Module 11: Run a training script as a command job in Azure Machine Learning

Convert a notebook to a script
Run a script as a command job
Use parameters in a command job

Module 12: Track model training with MLflow in jobs

Track metrics with MLflow
View metrics and evaluate models

Module 13: Run pipelines in Azure Machine Learning

Create components
Create a pipeline
Run a pipeline job

Module 14: Perform hyperparameter tuning with Azure Machine Learning

Define a search space
Configure a sampling method
Configure early termination
Use a sweep job for hyperparameter tuning

Module 15: Deploy a model to a managed online endpoint

Explore managed online endpoints
Deploy your MLflow model to a managed online endpoint
Deploy a model to a managed online endpoint

Module 16: Deploy a model to a batch endpoint

Understand and create batch endpoints
Deploy your MLflow model to a batch endpoint
Deploy a custom model to a batch endpoint
Invoke and troubleshoot batch endpoints

Documentation

Access to Microsoft Learn (online learning content)

Lab / Exercises

Official Microsoft Labs

Exam

This course prepares you to the exam DP-100: Designing and Implementing a Data Science Solution on Azure
If you wish to take this exam, please select it when you add the course to your basket

Complementary courses

Temptraining funding

ITTA is a partner of Temptraining, the continuing education fund for temporary workers. This training fund can subsidize continuing education for anyone who works for an employer subject to the Collective Work Agreement (CCT) Rental of services.