Welcome to Azure ML Fundamentals
This learning path is designed to provide you with a comprehensive understanding of Azure Machine Learning services. Whether you're a data scientist, developer, or IT professional, you'll gain the skills necessary to leverage the power of Azure for your machine learning projects.
We'll cover everything from setting up your workspace and preparing data to training models, deploying them as services, and monitoring their performance.
Learning Modules
- Module 1: Introduction to Azure Machine Learning
- Module 2: Setting Up Your Azure ML Workspace
- Module 3: Data Preparation and Feature Engineering
- Module 4: Training and Evaluating Machine Learning Models
- Module 5: Deploying Models as Web Services
- Module 6: Monitoring and Managing Deployed Models
- Module 7: Responsible AI and Ethical Considerations
Key Concepts Covered
- Azure ML Workspace
- Datasets and Data Assets
- Compute Targets (Compute Instances, Clusters, Kubernetes)
- Experiments and Runs
- Models and Endpoints
- MLOps Principles
- Responsible AI Practices