Integration and Deployment of GenAI Models

About this course

Unlock the full power of AWS to deploy Machine Learning and Generative AI solutions!

In this hands-on course, you’ll learn how to use AWS SageMaker, Amazon Bedrock, and Anthropic Claude models to build, train, and deploy intelligent applications.

We’ll start with setting up your AWS environment and mastering SageMaker's capabilities, from no-code tools like SageMaker Canvas to coding solutions using the Python SDK. You’ll then dive into Amazon Bedrock to work with foundation models (FMs) for text and image generation, and implement Retrieval-Augmented Generation (RAG) techniques.

Finally, you’ll explore Anthropic Claude — learning how to generate text, use role-based AI assistants, and build multimodal (text + image) applications through APIs.

Throughout the course, you’ll work on real-world projects including text generation, image generation, and fine-tuning large language models.

By the end of this course, you will be confident in setting up, managing, and deploying machine learning and AI models using AWS services — whether you are a data scientist, AI developer, cloud engineer, or tech enthusiast.

Key Topics Covered:

AWS Account Setup and SageMaker Studio EnvironmentNo-Code ML Model Building with SageMaker CanvasModel Deployment with Canvas and SageMaker SDKUsing Amazon Bedrock for Fully Managed Foundation ModelsComparing SageMaker vs. Bedrock for AI Deployments

Building AI Projects: Text Generation, Image Generation, RAG Fine-TuningWorking with Anthropic Claude for API-based Text and Image ApplicationsNo prior cloud deployment experience is required — just basic Python knowledge and a passion for machine learning and AI!

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