Prepare for DP-100: Data Science on Microsoft Azure Exam

Microsoft Certifications give you a professional edge by providing globally recognized and industry-approved evidence of mastery of digital and cloud business skills. In this course, you will prepare to pass the DP-100 Azure Data Scientist Associate certification exam. You will refresh your knowledge on how to plan and create a suitable production environment for data science workloads on Azure, conduct data experiments, and train predictive models. You will also learn how to manage, optimize, and deploy machine learning models in production. You will test your knowledge with a hands-on exam covering all the core topics covered in the DP-100 exam, ensuring you are well prepared to succeed in the certification. You will also gain a deeper understanding of the Microsoft certification program and where you can go next in your career. In addition, you will receive tips and tricks, testing strategies, helpful resources, and information on how to enroll in the DP-100 proctored exam. By the end of this course, you will be ready to enroll in and pass the DP-100 exam. This is the fifth course in a five-course program that prepares you for DP-100: The certification exam validates your knowledge and experience with machine learning solutions at cloud scale using Azure Machine Learning. This specialization teaches you how to use your existing knowledge of Python and machine learning to manage data ingest and preparation, train and deploy models, and monitor machine learning solutions on Microsoft Azure. Each course teaches you the concepts and skills that are measured on the exam. This specialization is designed for data scientists who have knowledge of Python and machine learning frameworks such as Scikit-Learn, PyTorch, and Tensorflow and want to build and operate machine learning solutions in the cloud. This course teaches data scientists how to build end-to-end solutions on Microsoft Azure. Students will learn how to manage Azure resources for machine learning; run experiments and train models; deploy and operationalize machine learning solutions; and implement responsible machine learning. They will also learn how to use Azure Databricks for data exploration, preparation, and modeling, and how to integrate Databricks machine learning workflows with Azure Machine Learning.