Generative AI for AWS Cloud Engineers

Overview

Generative AI for AWS Cloud Engineers course is designed for technical professionals aiming to master the integration, deployment, and optimization of large language models (LLMs) within the AWS cloud infrastructure. It aims to bridge the gap between traditional cloud engineering and the rapidly evolving landscape of generative AI. This course facilitates learners with approximately 4:00–5:00 Hours of Video lectures that provide a deep dive into both architectural theory and hands-on implementation. The course is structured into 3 Comprehensive Modules, with each module further split into technical lessons. To test the practical understanding of learners, every module includes Quizzes, and In-Video Knowledge Checks. Enroll in our “Generative AI for AWS Cloud Engineers” course to lead the next generation of cloud-native AI innovation. - Module 1: Gen AI on AWS - Amazon Bedrock - Module 2: Security and Governance of AI Solutions This course is specifically designed for technical professionals and cloud practitioners who aim to bridge the gap between core infrastructure and modern AI implementation. By the end of this course, a learner will be able to: - Understand foundational concepts, methods, and strategies related to artificial intelligence (AI), machine learning (ML), and generative AI (Gen AI) within the AWS ecosystem. - Identify appropriate AI/ML and generative AI technologies to address specific organizational use cases effectively. - Apply responsible practices in the utilization of AI, ML, and Generative AI technologies.

Syllabus

Gen AI on AWS - Amazon Bedrock

Welcome to Week 1 of the Generative AI for AWS Cloud Engineers course. This week, we will explore the Amazon Bedrock, starting with a comprehensive overview and hands-on demos to understand how to leverage FMs within the AWS ecosystem. You will learn how to customize models through Fine-tuning and implement advanced architectures like Retrieval-Augmented Generation (RAG) to enhance model accuracy with external data. By the end of this module, you will be able to configure Guardrails to ensure responsible AI usage, orchestrate complex tasks with Amazon Bedrock Agents, and navigate the Pricing structures to build cost-effective Generative AI solutions.

Security and Governance of AI Solutions

Welcome to Week 2. This week, we will explore the foundational principles and ethical practices required to build and deploy Responsible AI systems. We will learn how to select models using responsible criteria and navigate the complex legal risks associated with generative AI. Furthermore, we will dive into the AWS Shared Responsibility Model as it applies to AI, identifying specific AWS tools and services designed to secure AI systems and ensure robust governance. By the end of this week, you will be able to implement security and privacy considerations effectively to manage and protect your AI applications within the AWS ecosystem.