D8aland Mini Course: Amazon SageMaker Custom Configuration
D8aland Mini Course: Amazon SageMaker Custom Configuration
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 1h 33m | 609 MB
Instructor: Joe Cline
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 1h 33m | 609 MB
Instructor: Joe Cline
Just enough overview of the technology with demos on how to create lifecycles scripts and custom JupyterLab images
What you'll learn
- What SageMaker is
- The SageMaker and SageMaker Studio interface
- The Studio JupyterLab environment
- The training, inference, and deployment features in SageMaker
- What the BASH shell is
- Understand AWS IAM permissions and policies for SageMaker
- What a SageMaker Lifecycle Script is and how it’s structured
- Create and configure SageMaker Lifecycle configuration scripts
- What SageMaker images are
- What Docker is
- The difference between containerization and virtual machines
- What container repositories are
- When to use a lifecycle script or a custom image
- Best practices for creating and deploying lifecycle scripts and custom images
- How to create a Docker container build environment with EC2 and ECR
- Create and configure a SageMaker Custom Image
Requirements
- Basic AWS familiarity is preferred but not required
- Knowlege of BASH and Linux helpful but not required
- Basic understanding of Docker helpful but not required
- Knowledge of basic Python helpful but not required
Description
Do you need to customize a SageMaker environment but don't have 40, 20, or even 10 hours to spend on training? I see plenty of other courses that teach how to create ML models in SageMaker, but NOT how to set it up and customize it.
Introducing, d8aland's new mini course on how to customize SageMaker
Our mini courses are designed to be under two hours so you can get to the information you need quickly. They are created for specific use-cases instead of just a lengthy, high level tech overview. In other words, "how do I. . .?"
For example: How do I . . .
Launch an AWS EC2 instance?
Build design and load an AWS RDS or Aurora database?
Create scheduled jobs with AWS Glue and Managed Apache Airflow?
There are some explainer videos, but only enough to understand what we are doing in the demonstrations and why. In this case, how to create a Studio domain, launch JupyterLab and, configure lifecycle scripts and custom images.
I hope you find great value in this course. Please shoot me an email if you have suggestions for this course or any other mini course you would like to see us make.
Best of luck,
Joe Cline
Who this course is for:
- Data scientist and analyst who build models in SageMaker but want to learn SageMaker customization
- AWS Cloud Platform Enginners who wants to set up a custom SageMaker environment
- Engineers who work on a cloud platform other than AWS and need to learn about the SageMaker service
D8aland Mini Course: Amazon SageMaker Custom Configuration
