- 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 Data Scientist Associate (DP-100) Professional Certificate
Launch Your Career in Data Science. Apply data science and machine learning to implement and run machine learning workloads on Azure.
Offered By
What you will learn
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.
Skills you will gain

About this Professional Certificate
Applied Learning Project
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.
What is a Professional Certificate?
Build the Skills to Get Job Ready
Whether you’re looking to start a new career, or change your current one, Professional Certificates on Coursera help you become job ready. Learn at your own pace, whenever and wherever it’s most convenient for you. Enroll today and explore a new career path with a 7 day free trial. You can pause your learning or end your subscription at any time.
Hands-On Projects
Apply your skills with hands-on projects and build a portfolio that showcases your job readiness to potential employers. You'll need to successfully finish the project(s) to earn your Certificate.
Earn a Career Credential
When you complete all of the courses in the program, you'll earn a Certificate to share with your professional network as well as unlock access to career support resources to help you kickstart your new career. Many Professional Certificates have hiring partners that recognize the Professional Certificate credential and others can help prepare you for a certification exam. You can find more information on individual Professional Certificate pages where it applies.

There are 5 Courses in this Professional Certificate
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.
Offered by

Microsoft
Our goal at Microsoft is to empower every individual and organization on the planet to achieve more.
Frequently Asked Questions
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