In this course students will gain the necessary knowledge about how to use Azure services to develop, train, and deploy, machine learning solutions. The course starts with an overview of Azure services that support data science. From there, it focuses on using Azure's premier data science service, Azure Machine Learning service, to automate the data science pipeline. This course is focused on Azure and does not teach the student how to do data science. It is assumed students already know that.
Pass the DP-100 Designing and Implementing a Data Science Solution on Azure exam to be awarded the Microsoft Certified: Azure Data Scientist Associate certification.
Students learn how to develop data models that solve business problems using Azure technologies.
The Azure Data Scientist applies their knowledge of data science and machine learning to implement and run machine learning workloads on Azure; in particular, using Azure Machine Learning Service. This entails planning and creating a suitable working environment for data science workloads on Azure, running data experiments and training predictive models, managing and optimizing models, and deploying machine learning models into production.
This course is 50% presentation and demonstration and 50% hands-on learning using Microsoft Azure.
What You Will Learn
Module 1: Introduction to Azure Machine Learning
Module 2: "No-code" Machine Learning with Designer
Module 3: Running Experiments and Training Models
Module 4: Working with Data
Module 5: Compute Contexts
Module 6: Orchestrating Operations with Pipelines
Module 7: Deploying and Consuming Models
Module 8: Training Optimal Models
Module 9: Interpreting Models
Module 10: Monitoring Models