DP-100T01: Designing and Implementing a Data Science Solution on Azure Course Overview

The DP-100T01: Designing and Implementing a Data Science Solution on Azure course provides an in-depth exploration of Azure's machine learning capabilities. It covers the entire data science process from Data preparation, Model training, Model deployment, and Model management. Learners will gain practical experience with Azure Machine Learning Service and Azure Machine Learning Studio, learning how to create, train, optimize, and deploy machine learning models at scale.

Throughout the course, participants will engage in hands-on labs, such as creating an Azure Machine Learning workspace, running experiments, working with Datastores and datasets, and orchestrating Machine learning workflows with Pipelines. They will also explore real-time and Batch inferencing, ensuring their models can respond promptly or handle large-scale processing.

By mastering Hyperparameter tuning, Automated Machine Learning, and Model interpretation, students will be well-equipped to build responsible AI solutions. They'll also delve into the best practices for Monitoring models to maintain optimal performance over time, using tools like Application Insights and Data drift monitoring. This course is ideal for aspiring and existing data scientists looking to harness the power of Azure to streamline and enhance their Machine learning workflows.