Developing your First ML Workflow

This course discusses how to use AWS services to train a model, deploy a model, and how to use AWS Lambda Functions, Step Functions to compose your model and services into an event-driven application.

• Introduction to Developing ML Workflows
• This lesson gives an introduction to the course, including prerequisites, final project, stakeholders, and tools & environment.
• SageMaker Essentials
• This lesson will go over SageMaker essential services such as training jobs, endpoints, batch transforms, and processing jobs.
• Designing Your First Workflow
• This lesson will discuss machine learning workflows and AWS tools such as Lambda, Step Function for building a workflow.
• Monitoring a ML Workflow
• This lesson will go over monitoring a machine learning workflow and some useful services within AWS to help you monitoring the healthy of data and machine learning models.
• Project: Build a ML Workflow For Scones Unlimited On Amazon SageMaker
• In the project, you will build and ship an image classification model with AWS SageMaker for Scones Unlimited, a scone-delivery-focused logistic company.