DP-100T00: Designing and Implementing a Data Science Solution on Azure
By Tyler Farmer
Studio Recording
July 17, 2023
Course Description
Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course 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.
Course Content
Course Introduction and Overview
Errors you might encounter in the Labs
Errors you might encounter in the Labs
01-Design a machine learning solution
Design a Data Ingestion Strategy
Design a Model Training Solution
Design a Model Deployment Solution
02-Explore the Azure Machine Learning solution
Explore Azure ML Workspace Resources and Assets
Lab 01: Explore the ML Workspace
Granting Permissions the an ML Workspace
Other Machine Learning Resources
Explore Developer Tools
Lab 02: Explore Developer Tools
03-Make data available in Azure Machine Learning
Make Data Available
Lab 03: Make Data Available
04-Work with compute in Azure Machine Learning
Work with Compute Targets
Lab 04: Work with Compute Resources in Azure ML
Work with Environments in Azure ML
Lab 05: Work with Environments in Azure ML
05-Use no-code machine learning with the Azure Machine Learning Designer
Explore data with the ML Designer
Train models with the ML Designer
Lab 06: Train a model with the ML Designer
06-Automate machine learning model selection with Azure Machine Learning
Explore Automated ML
Find the Best Classification Model with Automated ML
Lab 07: Find the Best Classification Model with Automated ML
07-Track model training with MLFlow
Track model training with MLFlow
Lab 08: Track model training with MLFlow
08-Train models with scripts in Azure Machine Learning
Running a Script as a Command Job
Lab 09: Running a Script as a Command Job
Track model training with MLFlow in jobs
Lab 10: Track model training with MLFlow in jobs
09-Optimize model training in Azure Machine Learning
Run Pipelines in Azure ML
Lab 11: Run Pipelines in Azure ML
Perform Hyperparameter Tuning with Sweep Jobs
Lab 12: Perform Hyperparameter Tuning with a Sweep Job
10-Manage and review models in Azure Machine Learning
Register an ML Flow Model
Lab 13: Log and Register Models with MLFLow
Manage & Compare models (Responsible AI)
Lab 14: Compare & Evaluate Models (Responsible AI Dashboard)
11-Deploy and consume models with Azure Machine Learning
Deploy a Model to a Managed Online Endpoint
Lab 15: Deploy a Model to a Managed Online Endpoint
Deploy a Model to a Batch Endpoint
Lab 16: Deploy a Model to a Batch Endpoint
12-Design a machine learning operations (MLOps) solution
12-Design a machine learning operations (MLOps) solution