Amazon SageMaker JumpStart Foundations

Amazon SageMaker JumpStart is a machine learning (ML) hub with foundation models, built-in algorithms, and prebuilt ML solutions. In this foundations course, you will learn how to discover foundation models that meet your requirements and deploy them using the console. Through a guided tutorial consisting of a narrated video, step-by-step instructions, and transcript, you will learn how to apply filters to identify model candidates for your use case.

• Course level: Intermediate
• Duration: 1 hour

Activities

This course includes demonstrations, videos, and knowledge check questions.

Course objectives

In this course, you will learn to do the following:

• Search the vast catalog of foundation models including large language models (LLMs) in the SageMaker JumpStart model hub, and select the right model for your use case.
• Deploy, fine-tune, and evaluate models using the SageMaker JumpStart console.
• Use deployment parameters and select instance types.
• Create generative images using text prompts.
• Cleanup the SageMaker resources you have created during demonstrations.

Intended Audience:

This course is intended for the following roles:

• Data scientists
• Machine learning engineers

Prerequisites

We recommend that attendees of this course have the following:

• Completed the AWS Technical Essentials course
• Knowledge of machine learning and training language models

Course outline

• Lesson 1: Course Navigation
• Lesson 2: Introduction
• Lesson 3: Discovering Foundation Models
• Lesson 4: Deploying Foundation Models
• Lesson 5: Assessment
• Lesson 6: Conclusion
• Lesson 7: Contact Us