Azure Data Scientist Associate DP-100 Certification Guide

Master machine learning with Azure and pass the DP-100 certification using real-world experiments, AutoML, and Generative AI tools.

Key Features

Build end-to-end machine learning pipelines using no-code and code-first approaches
Monitor, evaluate, and operationalize models with Azure ML and MLflow
Create powerful GenAI applications using Prompt Flow and deploy them at scale
Purchase of the print or Kindle book includes a free PDF eBook

Book DescriptionThe Azure Data Scientist Associate Certification Guide helps you acquire practical knowledge for machine learning experimentation on Azure. It covers everything you need to pass the DP-100 exam and become a certified Azure Data Scientist Associate.
Starting with foundational concepts in data science, you'll learn how to configure and use the Azure Machine Learning (Azure ML) workspace via both studio and SDK interfaces. You'll progress through no-code and low-code experimentation using AutoML and the visual designer, and delve into advanced Python SDK-based model training and deployment.
This book also introduces you to the power of Generative AI with Prompt Flow, enabling you to build intelligent agents and operationalize them for production use. You'll gain skills in hyperparameter tuning, model interpretation, and fairness analysis, and finally, deploy models as scalable endpoints with robust monitoring.
Complete with hands-on exercises, mock exams, and expert tips, this guide offers everything you need to tackle the DP-100 exam and apply your learnings in real-world data science scenarios.What you will learn

Provision a working environment for data science workloads in Azure
Run data experiments and train models using Azure ML services
Use AutoML and hyperparameter tuning to optimize models
Deploy and consume trained models in production
Monitor and interpret model behavior using responsible AI tools
Use Prompt Flow to build Generative AI agents

Who this book is forThis book is ideal for data scientists and developers seeking to scale their machine learning workloads in Azure and pass the DP-100 certification exam. Basic familiarity with Python and data science concepts is recommended for the second half of the book, while the initial chapters are beginner-friendly. Whether you're an aspiring Azure ML engineer or a professional needing to operationalize ML models, this guide provides the theory, practice, and insights to succeed.