What Does MVP Stand For? It’s Not What You Think.
October 7, 2024
Article
This course is part of multiple programs.
Instructor: Microsoft
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(213 reviews)
Recommended experience
Beginner level
General programming knowledge or experience would be beneficial. You need to have basic computer literacy and proficiency in the English language.
(213 reviews)
Recommended experience
Beginner level
General programming knowledge or experience would be beneficial. You need to have basic computer literacy and proficiency in the English language.
How to describe capabilities of no-code machine learning with Azure Machine Learning Studio
How to identify core tasks in creating a machine learning solution
How to describe core machine learning concepts
How to identify common machine learning types
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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 course will help you prepare for Exam AI-900: Microsoft Azure AI Fundamentals. This is the second course in a five-course program that prepares you to take the AI-900 certification exam. This course teaches you the core concepts and skills that are assessed in the AI fundamentals exam domains. This beginner course is suitable for IT personnel who are just beginning to work with Microsoft Azure and want to learn about Microsoft Azure offerings and get hands-on experience with the product. Microsoft Azure AI Fundamentals can be used to prepare for other Azure role-based certifications like Microsoft Azure Data Scientist Associate or Microsoft Azure AI Engineer Associate, but it is not a prerequisite for any of them. This course is intended for candidates with both technical and non-technical backgrounds. Data science and software engineering experience is not required; however, some general programming knowledge or experience would be beneficial. To be successful in this course, you need to have basic computer literacy and proficiency in the English language. You should be familiar with basic computing concepts and terminology, general technology concepts, including concepts of machine learning and artificial intelligence.
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 readings1 quiz2 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 readings1 quiz2 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.
2 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 Aug 14, 2024
Fantastic hands on experience with the right mix of repetition and new content
Reviewed on Jan 24, 2023
I would have preferred following the practical exercises via video or links to Microsoft videos should have been provided in an additional resources section
Reviewed on Oct 11, 2021
excellent course. it will better than if student don't have to register in Azure portal as GDP that GDP don't need to use credit card to done their lab.
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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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