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
- Free with your book: PDF Copy, AI Assistant, and Next-Gen Reader
Book Description
The Azure Data Scientist Associate DP-100 Certification Guide teaches you how to run machine learning experiments on Azure. It includes 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 explore advanced Python SDK-based model training and deployment. This second edition 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 develop practical 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 for preparing to sit for 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 for
This 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 looking to operationalize ML models, this guide provides the theory, practice, and insights to succeed.
