Azure ML: Explore & Configure the Machine Learning Workspace

The Exam Prep DP-100: Microsoft Certified Azure Data Scientist Associate course is designed for professionals aiming to apply data science and machine learning to Azure workloads. This course equips learners with the skills to design, implement, and optimize machine learning solutions using Azure Machine Learning, MLflow, and Azure AI services. Participants will gain hands-on experience in data ingestion, preparation, model training, deployment, and monitoring. Through practical demonstrations and real-world scenarios, the course ensures learners are prepared to build scalable AI solutions in Azure. The specialization is divided into four key courses, covering the domain requirements for the DP-100: Designing and Implementing a Data Science Solution on Azure exam: The detail of the Courses is provided below Course 1: Azure ML: Designing and Preparing Machine Learning Solutions Course 2: Azure ML: Explore & Configure the Machine Learning Workspace Course 3: Azure ML: Deploying, Managing, and Experimenting with Models Course 4:Azure AI & ML: Optimize Language Models for AI Applications These courses are further divided into Modules, Lessons, and Video Items. All the courses have a set of Practice and Graded assignments available that test the candidate's ability to understand the concepts and grasp the topics discussed in the courses. This course aims to achieve the Microsoft Certified: Azure Data Scientist Associate Certification. Some of the important benefits of achieving these certifications include: Industry Recognition: Validates expertise in Azure Machine Learning. Career Growth: Enhances job prospects in AI, ML, and cloud-based data science. Higher Earning Potential: Opens doors to high-paying roles in data science and AI

• Design, implement, and optimize machine learning solutions on Azure
• Gain hands-on experience in data ingestion and preparation
• Train, deploy, and monitor models using real-world scenarios

• Basic familiarity with the topic and its common terminology
• Readiness to practice through applied exercises or case-based work