Developing your First ML Workflow training
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.
Skills you'll learn
AWS lambda ? Sagemaker processing ? Sagemaker batch transform jobs ? Sagemaker training jobs
Prerequisite Details
To optimize your success in this program, we've created a list of prerequisites and recommendations to help you prepare for the curriculum. Prior to enrolling, you should have the following knowledge:
Course Lessons
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.
contact us
email - [email protected]