This course provides essential knowledge for developing, training, and deploying machine learning solutions using Azure services. You will begin with a comprehensive overview of Azure services that support data science work, then focus on the Azure Machine Learning service, the platform's premier data science tool, which enables you to automate the complete data science pipeline. This course concentrates specifically on Azure platform capabilities and does not teach foundational data science methods. It is assumed you already possess knowledge of data science principles and practices.
Intended Audience:
This course is designed for data scientists and professionals with significant responsibility for training and deploying machine learning models in production environments.
Course Prerequisites:
Before beginning this course, participants should have:
- Understanding of Azure fundamentals and core Azure services
- Knowledge of data science fundamentals, including data preparation techniques, model training approaches, and how to evaluate and compare models to identify the most effective solution
- Practical programming experience in Python, including proficiency with key libraries such as pandas, scikit-learn, matplotlib, and seaborn
Course Modules:
- Module 1: Doing Data Science on Azure. Explore how to conduct data science projects using Azure's comprehensive service ecosystem
- Module 2: Doing Data Science with Azure Machine Learning Service. Learn to implement data science workflows using Azure Machine Learning, the platform's premier service
- Module 3: Automate Machine Learning with Azure Machine Learning Service. Master techniques for automating the machine learning pipeline to increase efficiency and consistency
- Module 4: Manage and Monitor Machine Learning Models with the Azure Machine Learning Service. Develop skills for maintaining deployed models, monitoring performance, and ensuring ongoing effectiveness
