Exam Ref DP-100 Designing and Implementing a Data Science Solution on Azure
by Dayne Sorvisto (Author)
Publisher finelybook 出版社: Microsoft Press; 1st edition (November 1, 2024)
Language 语言: English
Print Length 页数: 192 pages
ISBN-10: 0135350603
ISBN-13: 9780135350607
Book Description
Prepare for Microsoft Exam DP-100 and demonstrate your real-world knowledge of managing data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Python, Azure Machine Learning, and MLflow. Designed for professionals with data science experience, this Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified: Azure Data Scientist Associate level.
Focus on the expertise measured by these objectives:
- Design and prepare a machine learning solution
- Explore data and train models
- Prepare a model for deployment
- Deploy and retrain a model
This Microsoft Exam Ref:
- Organizes its coverage by exam objectives
- Features strategic, what-if scenarios to challenge you
- Assumes you have experience in designing and creating a suitable working environment for data science workloads, training machine learning models, and managing, deploying, and monitoring scalable machine learning solutions
About the Exam
Exam DP-100 focuses on knowledge needed to design and prepare a machine learning solution, manage an Azure Machine Learning workspace, explore data and train models, create models by using the Azure Machine Learning designer, prepare a model for deployment, manage models in Azure Machine Learning, deploy and retrain a model, and apply machine learning operations (MLOps) practices.
About Microsoft Certification
Passing this exam fulfills your requirements for the Microsoft Certified: Azure Data Scientist Associate credential, demonstrating your expertise in applying data science and machine learning to implement and run machine learning workloads on Azure, including knowledge and experience using Azure Machine Learning and MLflow.
About the Author
Dayne Sorvisto is a seasoned data engineer and technical author (MLOps Lifecycle Toolkit). Dayne has held senior technical positions including Staff Data Engineer, Software Developer, and Senior Machine Learning Engineer, and has a Master’s degree in Pure Mathematics. You can connect with Dayne on LinkedIn at linkedin.com/in/daynesorvisto or visit his website wyattsolutions.co to learn more.
