AWS DevOps and AI Foundation: Automating Cloud Workflows

As software development evolves, the intersection of cloud automation and artificial intelligence has become essential for modern engineering teams. Understanding how to deploy, manage, and scale AI-powered applications using robust DevOps practices is a highly sought-after skill. This text-based course guides you from cloud development fundamentals to deploying automated, intelligent systems. You will learn how to bridge the gap between development, operations, and machine learning, enabling you to build resilient pipelines and leverage cloud-native AI services effectively. What you'll learn: - Understand foundational DevOps concepts, cloud architecture, and essential terminology. - Configure continuous integration and continuous delivery (CI/CD) pipelines to automate software deployment. - Implement Infrastructure as Code (IaC) patterns to manage cloud resources programmatically. - Integrate cloud-native AI services and Amazon Bedrock to add intelligent features to your applications. - Apply MLOps basics to monitor, scale, and maintain AI models in production environments. - Practice troubleshooting and observability techniques to ensure system reliability. The curriculum begins with core cloud and DevOps definitions before guiding you through pipeline automation, infrastructure management, and AI service integration. Through structured written explanations and practical code examples, you will gain a clear roadmap for deploying intelligent systems. This course is designed for beginners, software developers, and aspiring systems administrators who want to learn cloud automation and AI integration without needing prior DevOps experience. Start reading today to build your foundation in automated, AI-driven cloud operations.