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所在平台: Udemy |
课程主页: https://www.udemy.com/course/integration-and-deployment-of-genai-models-l/
课程评论：没有评论
课程名称：生成式人工智能模型的集成与部署 课程概述： 在本课程中，您将全面掌握 AWS 的能力，以便有效地部署机器学习和生成式人工智能解决方案！这是一个实践性强的课程，您将学习如何使用 AWS SageMaker、Amazon Bedrock 和 Anthropic Claude 等模型来构建、训练和部署智能应用程序。课程内容包括设置 AWS 环境，掌握 SageMaker 的功能，从无代码工具 SageMaker Canvas 到用 Python SDK 的编码解决方案。接下来，您将深入了解 Amazon Bedrock，利用基础模型（FMs）进行文本和图像生成，并实现增强检索生成（RAG）技术。最后，您将探索 Anthropic Claude，学习如何生成文本，使用基于角色的 AI 助手，以及通过 API 构建多模态（文本 + 图像）应用程序。 在整个课程中，您将参与包括文本生成、图像生成和大型语言模型微调在内的真实项目。完成本课程后，您将自信地设置、管理和部署使用 AWS 服务的机器学习和人工智能模型，无论您是数据科学家、人工智能开发者、云工程师还是科技爱好者。 关键主题涵盖： - AWS 账户设置与 SageMaker Studio 环境 - 使用 SageMaker Canvas的无代码机器学习模型构建 - 使用 Canvas 和 SageMaker SDK 进行模型部署 - 利用 Amazon Bedrock 实现全托管基础模型 - 将 SageMaker 与 Bedrock 进行 AI 部署的比较 - 构建 AI 项目：文本生成、图像生成、RAG 微调 - 使用 Anthropic Claude 进行基于 API 的文本和图像应用 本课程不要求先前的云部署经验，仅需具备基本的 Python 知识和对机器学习及人工智能的热情！
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 DeploymentsBuilding 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!
