Build and Operate Machine Learning Solutions with Azure
This course provides an introduction to Azure Machine Learning, teaching students how to use the Python SDK to build and operate ML solutions in the cloud. Students will gain the skills to create, deploy, manage, and monitor enterprise-ready ML models with Azure. ▼
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Course Feature
Cost:
Free
Provider:
Coursera
Certificate:
Paid Certification
Language:
English
Start Date:
22nd May, 2023
Course Overview
❗The content presented here is sourced directly from Coursera platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [February 21st, 2023]
What does this course tell?
(Please note that the following overview content is from the original platform)
Azure Machine Learning is a cloud platform for training, deploying, managing, and monitoring machine learning models. In this course, you will learn how to use the Azure Machine Learning Python SDK to create and manage enterprise-ready ML solutions.
This is the third course in a five-course program that prepares you to take the DP-100: Designing and Implementing a Data Science Solution on Azurecertification exam.
The certification exam is an opportunity to prove knowledge and expertise operate machine learning solutions at a cloud-scale using Azure Machine Learning. This specialization 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. Each course teaches you the concepts and skills that are measured by the exam.
This Specialization is intended 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. It teaches data scientists how to create end-to-end solutions in Microsoft Azure. Students will learn how to manage Azure resources for machine learning; run experiments and train models; deploy and operationalize machine learning solutions, and implement responsible machine learning. They will also learn to use Azure Databricks to explore, prepare, and model data; and integrate Databricks machine learning processes with Azure Machine Learning.What can you get from this course?
We consider the value of this course from multiple aspects, and finally summarize it for you from three aspects: personal skills, career development, and further study:
(Kindly be aware that our content is optimized by AI tools while also undergoing moderation carefully from our editorial staff.)
What skills and knowledge will you acquire during this course?
This course will provide learners with the skills and knowledge to create and manage enterprise-ready ML solutions using the Azure Machine Learning Python SDK. Learners will gain an understanding of how to leverage 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. Additionally, learners will learn how to create end-to-end solutions in Microsoft Azure, including managing Azure resources for machine learning, running experiments and training models, deploying and operationalizing machine learning solutions, and implementing responsible machine learning. Finally, learners will gain an understanding of how to use Azure Databricks to explore, prepare, and model data, and integrate Databricks machine learning processes with Azure Machine Learning.
How does this course contribute to professional growth?
This course provides learners with the knowledge and skills to build and operate machine learning solutions with Azure. It covers topics such as using the Azure Machine Learning Python SDK to create and manage enterprise-ready ML solutions, leveraging 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, creating end-to-end solutions in Microsoft Azure, and using Azure Databricks to explore, prepare, and model data. By taking this course, learners can gain the skills necessary to develop and manage machine learning solutions in Azure, which can contribute to their professional growth.
Is this course suitable for preparing further education?
This course is suitable for preparing further education in the field of machine learning. It provides learners with the knowledge and skills to create and manage enterprise-ready ML solutions in Microsoft Azure. Learners will gain an understanding of data ingestion and preparation, model training and deployment, and machine learning solution monitoring. They will also learn how to use Azure Databricks to explore, prepare, and model data, and integrate Databricks machine learning processes with Azure Machine Learning. This course is an excellent foundation for further study in the field of machine learning.
Pros & Cons
Access to Microsoft Learn materials.
Comprehensive coverage of Azure ML.
Easy to follow exercises.
No Azure subscription provided.
Limited value added.
Exercises from Microsoft Learn.
Course Provider
Provider Coursera's Stats at AZClass
Discussion and Reviews
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