For the Microsoft DP-100 Exam, titled "Designing and Implementing a Data Science Solution on Azure," candidates should possess expertise in applying data science and machine learning to implement and run machine learning workloads on Azure. The exam is designed for data scientists who use Azure Machine Learning and MLflow to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring.

Key areas covered in the exam include:

• Designing and preparing a machine learning solution (20–25%)
• Exploring data and training models (35–40%)
• Preparing a model for deployment (20–25%)
• Deploying and retraining a model (10–15%)

Candidates will be evaluated on their ability to design a suitable working environment for data science workloads, explore data, train machine learning models, implement pipelines, run jobs for production, and manage, deploy, and monitor scalable machine learning solutions.