Azure Data Scientist Associate (DP-100) Duration: 3 days Teaching method: classroom live and virtual classroom Objectives | Audience | Prerequisites | Topics | Schedule Gain the necessary knowledge about how to use Azure services to develop, train, and deploy, machine learning solutions. The course starts with an overview of Azure services that support data science. From there, it focuses on using Azure’s premier data science service, Azure Machine Learning service, to automate the data science pipeline. This course is focused on Azure and does not teach the student how to do data science. It is assumed students already know that. OBJECTIVES Rampup in order to pass for for exam DP-100 ‘Designing and Implementing a Data Science Solution on Azure’. This earns you the cerfication Microsoft Certified: Azure Data Scientist Associate. AUDIENCE This course is aimed at data scientists and those with significant responsibilities in training and deploying machine learning models. PREREQUISITES Microsoft Azure Fundamentals (AZ-900) or an equivalent of this course. Before attending this course, students must have: Azure Fundamentals Understanding of data science including how to prepare data, train models, and evaluate competing models to select the best one. How to program in the Python programming language and use the Python libraries: pandas, scikit-learn, matplotlib, and seaborn. TOPICS Module 1: Doing Data Science on Azure Introduce the Data Science Process Overview of Azure Data Science Options Introduce Azure Notebooks Module 2: Doing Data Science with Azure Machine Learning service Introduce Azure Machine Learning (AML) service Register and deploy ML models with AML service Module 3: Automate Machine Learning with Azure Machine Learning service Automate Machine Learning Model Selection Automate Hyperparameter Tuning with HyperDrive Module 4: Manage and Monitor Machine Learning Models with the Azure Machine Learning service Manage and Monitor Machine Learning Models SCHEDULE Contact Gelieve dit veld leeg te laten.Send
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