Practical Generative AI on AWS

Ready to move beyond AI theory and build real applications? This course shows you how to harness the power of Generative AI and Large Language Models (LLMs) on the AWS cloud, turning your ideas into production-ready solutions. You will gain the practical skills to select, deploy, and manage LLMs for your own projects. You'll learn to build robust, scalable, and cost-effective AI applications by leveraging the core services and best practices of the AWS ecosystem. What you'll learn: - Understand the core concepts of Generative AI, LLMs, and foundational AWS services like Bedrock and SageMaker. - Build a practical Retrieval-Augmented Generation (RAG) application to connect LLMs with your own data sources. - Apply fundamental prompt engineering techniques to control and improve model outputs for specific tasks. - Deploy LLM-powered applications using containerization and modern cloud practices for scalability. - Configure essential monitoring and logging to track application performance and ensure reliability in production. - Learn cost and performance optimization strategies for running AI workloads efficiently on AWS. The course begins with the essential terminology and architecture of LLMs, then moves into hands-on exercises with key AWS services. You'll progress from basic model interaction to building and deploying a complete, scalable application. This course is designed for beginners. No prior experience with AI, machine learning, or AWS is required to get started. Start building your first cloud-native AI application today.