About This Course
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.
By completing these labs, users will have good knowledge of cloud concepts and Azure services.
Users should be familiar with the general technology concepts, including concepts of networking, storage, compute, application support, and application development, Azure ML Workspace, and Machine learning.
These hands-on labs are provided with a ready-to-use Azure environment along with detailed personalized instructions to learn and complete the exercises to prepare for DP-100 certification.
DP-100 package includes access to Azure environment along with lab instructions for completing the following modules.
Modules for DP-100 Course Included:
Introduction to Azure Machine Learning
Use Automated Machine Learning
Azure ML Designer
Work with Data
Work with Compute
Create a Pipeline
Create a Real-time Inference Service
Create a Batch Inferencing Service
Use Automated Machine Learning from the SDK
Explore Differential Privacy
Detect and Mitigate Unfairness
Monitor a Model
Monitor Data Drift
Note: For performing the labs, you need to ensure you are clicking on the Launch Lab button only when you are ready to perform the lab as you will be able to launch the lab only once.
This course doesn’t have any technical pre-requisite. This course primarily uses the Azure portal to create services and does not require scripting skills.