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January 28, 2025
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This course is part of Microsoft Azure Data Scientist Associate (DP-100) Exam Prep Professional Certificate
Instructor: Microsoft
13,952 already enrolled
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(157 reviews)
Recommended experience
Intermediate level
General programming knowledge or experience would be beneficial. You need to have basic computer literacy and proficiency in the English language.
(157 reviews)
Recommended experience
Intermediate level
General programming knowledge or experience would be beneficial. You need to have basic computer literacy and proficiency in the English language.
Identify different kinds of machine learning models
How to use the automated machine learning capability of Azure Machine Learning to train and deploy a predictive model
Create regression, classification, and clustering models using Azure Machine Learning designer
Use Azure Machine Learning to create and publish models without writing code
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Machine learning is at the core of artificial intelligence, and many modern applications and services depend on predictive machine learning models. Training a machine learning model is an iterative process that requires time and compute resources. Automated machine learning can help make it easier. In this course, you will learn how to use Azure Machine Learning to create and publish models without writing code.
This is the second 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.
Training a machine learning model is an iterative process that requires time and compute resources. Automated machine learning can help make it easier. In this module, you'll learn how to identify different kinds of machine learning model and how to use the automated machine learning capability of Azure Machine Learning to train and deploy a predictive model.
3 videos8 readings3 assignments1 discussion prompt1 plugin
Regression is a supervised machine learning technique used to predict numeric values. In this module, you will learn how to create regression models using Azure Machine Learning designer.
2 videos8 readings3 assignments
Classification is a supervised machine learning technique used to predict categories or classes. In this module, you will learn how to create classification models using Azure Machine Learning designer.
2 videos8 readings3 assignments
Clustering is an unsupervised machine learning technique used to group similar entities based on their features. In this module, you will learn how to create clustering models using Azure Machine Learning designer.
3 videos9 readings3 assignments1 discussion prompt
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
Our goal at Microsoft is to empower every individual and organization on the planet to achieve more. In this next revolution of digital transformation, growth is being driven by technology. Our integrated cloud approach creates an unmatched platform for digital transformation. We address the real-world needs of customers by seamlessly integrating Microsoft 365, Dynamics 365, LinkedIn, GitHub, Microsoft Power Platform, and Azure to unlock business value for every organization—from large enterprises to family-run businesses. The backbone and foundation of this is Azure.
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Reviewed on Jan 3, 2024
Some exercises had outdated instructions, considering the recent updates in Azure Machine Learning services.
Reviewed on Feb 13, 2024
very easy to follow module...I love the hands-on practice with the Microsoft Azure Platform as well
Reviewed on Apr 24, 2024
Easy to understand and very good explanation from the instructor
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IT professionals interested in learning about the types of solutions artificial intelligence (AI) makes possible, and the services on Microsoft Azure that you can use to create them.
Working IT professionals looking for additional skills or credentials to demonstrate knowledge of common ML and AI workloads and how to implement them on Azure. IT professionals looking to specialize in the specific area of Artificial intelligence on Azure.
Machine learning is at the core of artificial intelligence, and many modern applications and services depend on predictive machine learning models. Training a machine learning model is an iterative process that requires time and compute resources. Automated machine learning can help make it easier. In this course, you will learn how to use Azure Machine Learning to create and publish models without writing code.
You should expect to spend at least an hour every week for four weeks to complete all aspects of this course.
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