Microsoft Azure is a set of cloud computing services that constantly continues to grow. Azure helps your organization solve all kinds of business challenges. With Azure, your organization has the freedom to use your favourite tools and frameworks to develop, manage, and implement applications on a large, global network.
During the course Designing and Implementing a Data Science Solution on Azure | DP-100 (via e-learning) you learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course 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.
This course is focused on Azure and does not teach the student how to do data science. It is assumed students already know that.
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This course is designed 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.
Before attending this course students must have: - a fundamental knowledge of Microsoft Azure; - experience of writing Python code to work with data, using libraries such as Numpy, Pandas, and Matplotlib; - understanding of data science, including how to prepare data, and train machine learning models using common machine learning libraries such as Scikit-Learn, PyTorch, or Tensorflow; - working with containers. If you are completely new to data science and machine learning, please complete the course Microsoft Azure AI Fundamentals | AI-900 (via e-learning) first.
This course concerns self-study. You determine the study duration yourself. You have access to the training for one year.
After the course you can participate in the exam. The course helps to prepare for exam DP-100. The exam fees amount € 200,00 and are not included.
