- Manage Azure resources for machine learning
- Deploy and operationalize machine learning solutions
- Run experiments and train models
- Implement responsible machine learning
- Machine Learning
- Supervised Learning
- Regression Analysis
- regression
- Work with Data and Compute in Azure Machine Learning
- Use the Azure Machine Learning SDK to train a model
- Select models and protect sensitive data
- Orchestrate pipelines and deploy real-time machine learning services with Azure Machine Learning
Microsoft Azure 데이터 과학 어소시에이트(DP-100) 전문 자격증
데이터 과학 부문의 경력을 시작하세요. Apply data science and machine learning to implement and run machine learning workloads on Azure.
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배울 내용
Manage Azure resources for machine learning
Run experiments and train models
Deploy and operationalize ethical machine learning solutions
How to plan and create a working environment for data science workloads on Azure and how to run data experiments and train predictive models.
귀하가 습득할 기술

이 전문 자격증 정보
응용 학습 프로젝트
Learners will engage in interactive exercises throughout this program that offers opportunities to practice and implement what they are learning. They will work directly in the Azure Portal and use the Microsoft Learn Sandbox. This is a free environment that allows learners to explore Microsoft Azure and get hands-on with live Microsoft Azure resources and services. For example, when you learn about training a deep neural network; you will work in a temporary Azure environment called the Sandbox. The beauty about this is that you will be working with real technology but in a controlled environment, which allows you to apply what you learn, and at your own pace. You will need a Microsoft account. If you don't have one, you can create one for free. The Learn Sandbox allows free, fixed-time access to a cloud subscription with no credit card required. Learners can safely explore, create, and manage resources without the fear of incurring costs or "breaking production".
Some experience in training machine learning models with Python and open-source frameworks like Scikit-Learn, PyTorch, and Tensorflow.
Some experience in training machine learning models with Python and open-source frameworks like Scikit-Learn, PyTorch, and Tensorflow.
전문 자격증이란 무엇인가요?
기술을 쌓아서 실무에 대비
새로운 분야에서 커리어를 찾고 있거나 현재 커리어에 변화를 주고 싶다면, Coursera의 전문 자격증을 취득하여 준비된 인재로 거듭날 수 있습니다. 가장 편리한 시간과 장소에서 나에게 맞는 속도로 배워보세요. 지금 바로 등록하고 7일 무료 평가판을 통해 새로운 진로를 탐색해보세요. 언제든지 학습을 일시 중지하거나 구독을 종료할 수 있습니다.
실습 프로젝트
실습 프로젝트에서 기술을 적용해보고, 미래 고용주에게 실무적으로 준비된 인재임을 보여주는 포트폴리오를 만들어보세요. 자격증을 취득하려면 프로젝트를 성공적으로 완료해야 합니다.
경력 자격 증명 취득
프로그램의 모든 강좌를 완료하면 전문가 네트워크에서 공유할 수 있는 자격증을 얻게 되며, 새로운 커리어를 시작하는 데 도움이 되는 커리어 지원 리소스에 액세스할 수 있게 됩니다. 많은 전문 자격증은 해당 전문 자격증의 자격 증명을 인정해주는 채용 파트너가 있거나, 자격증 시험을 준비하는 데 도움이 됩니다. 해당하는 경우 개별 전문 자격증 페이지에서 자세한 내용을 알아볼 수 있습니다.

이 전문 자격증에는 5개의 강좌가 있습니다.
Create Machine Learning Models in Microsoft Azure
Machine learning is the foundation for predictive modeling and artificial intelligence. If you want to learn about both the underlying concepts and how to get into building models with the most common machine learning tools this path is for you. In this course, you will learn the core principles of machine learning and how to use common tools and frameworks to train, evaluate, and use machine learning models.
Microsoft Azure Machine Learning for Data Scientists
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.
Build and Operate Machine Learning Solutions with Azure
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.
Perform data science with Azure Databricks
In this course, you will learn how to harness the power of Apache Spark and powerful clusters running on the Azure Databricks platform to run data science workloads in the cloud.
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Microsoft
Our goal at Microsoft is to empower every individual and organization on the planet to achieve more.
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