Building Generative AI with AWS: Amazon Q Developer, Bedrock Inference, and SageMaker Canvas
Building Generative AI with AWS: Amazon Q Developer, Bedrock Inference, and SageMaker Canvas
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 1h 23m | 163 MB
Instructor: Noah Gift
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 1h 23m | 163 MB
Instructor: Noah Gift
In this course, MLOps expert Noah Gift guides you through the world of generative AI on AWS. Build your understanding of tokenization, multiple model architecture, and how AI models are built and deployed. Discover the innovative Retrieval-Augmented Generation (RAG) technique and see its implementation on AWS using Bedrock knowledge agents. Get hands-on with Amazon Q developer tools, including installation and development using IntelliJ and VS Code, as well as features like the documentation assistant and code scanning. Dive deeper into AWS Bedrock with lessons on provisioned IO and evaluating prompts. Familiarize yourself with SageMaker Canvas, a robust environment for working with datasets and MLOps. By the end of this course, you will be proficient in leveraging various AWS tools to optimize your AI and machine learning workflows.
Building Generative AI with AWS: Amazon Q Developer, Bedrock Inference, and SageMaker Canvas
