DP-100T01-A | Designing and Implementing a Data Science Solution on Azure

DP-100T01-A | Designing and Implementing a Data Science Solution on Azure


About this course    
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.


Prerequisites
Successful Azure Data Scientists start this role with a fundamental knowledge of cloud computing concepts, and experience in general data science and machine learning tools and techniques.
Specifically:
•    Creating cloud resources in Microsoft Azure.
•    Using Python to explore and visualize data.
•    Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow.
•    Working with containers

 

Audience profile    
This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud.


COURSE OUTLINE

 

 

Module 1: Getting Started with Azure Machine Learning

 

Module 2: No-Code Machine Learning

 

Module 3: Running Experiments and Training Models

 

Module 4: Working with Data

 

Module 5: Working with Compute

 

Module 6: Orchestrating Operations with Pipelines

 

Module 7: Deploying and Consuming Models

 

Module 8: Training Optimal Models

 

Module 9: Responsible Machine Learning

 

Module 10: Monitoring Models

DP-100T01-A | Designing and Implementing a Data Science Solution on Azure

SKU: MICROSOFT-DP-100T01-A
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