Cloud AI Fundamentals: Understand and Build Generative Models

Artificial intelligence is transforming how we work and build, but getting started with cloud-based AI can feel overwhelming. This course demystifies the core concepts, giving you a clear, step-by-step path to understanding and using modern generative AI tools. You will transition from a curious beginner to a confident practitioner who understands how artificial intelligence operates in cloud environments. By exploring foundational definitions, ethical frameworks, and practical applications, you will gain the vocabulary and practical skills needed to navigate the modern AI landscape. What you'll learn: - Understand foundational AI terminology, including the core differences between Large Language Models (LLMs) and Foundation Models (FMs). - Explore how artificial intelligence models are hosted, scaled, and accessed in cloud environments. - Apply basic prompt engineering techniques to interact effectively with generative models. - Discover the principles of responsible AI, including bias mitigation, privacy, and ethical implementation. - Create functional, no-code AI applications using cloud-based playground environments like PartyRock. - Learn the fundamentals of modern AI architectures, including introductory concepts like Retrieval-Augmented Generation (RAG). The course begins with essential terminology and the mechanics of cloud-hosted models before guiding you through ethical considerations and hands-on, text-based building exercises. You will read clear explanations, analyze model configurations, and practice designing your own AI-driven solutions through written exercises. This course is designed for absolute beginners with no prior programming or cloud computing experience who want to understand the fundamentals of modern AI. Start reading today to build a strong foundation in cloud-based artificial intelligence.