Introduction to AI and Machine Learning on the Cloud

Cloud computing has democratized artificial intelligence, making powerful machine learning tools accessible to everyone without the need for expensive hardware. This text-based course guides you through the foundational concepts of cloud-based AI, helping you understand how to leverage pre-trained models, custom training pipelines, and modern generative AI tools. You will transition from understanding basic machine learning terminology to confidently identifying which cloud services fit your specific business or technical needs. By reading through practical scenarios and clear architectural explanations, you will gain the knowledge required to plan and execute cloud-aligned AI projects. What you'll learn: Learn core machine learning concepts, including supervised, unsupervised, and reinforcement learning; Explore cloud-based AI services, from pre-built APIs for vision and translation to custom model builders; Understand how data pipelines feed machine learning models and how to manage data preparation on the cloud; Discover modern generative AI workflows, including large language models (LLMs) and prompt engineering basics; Learn the fundamentals of retrieval-augmented generation (RAG) and cloud-hosted vector databases; Evaluate model evaluation metrics and cloud deployment strategies for real-time predictions. The course begins with essential definitions and foundational AI concepts before moving into practical cloud architectures and modern deployment workflows. You will progress through structured text lessons designed to build your conceptual and practical framework step-by-step. This course is designed for absolute beginners, business professionals, and developers looking to understand cloud AI capabilities without any prior machine learning or programming experience. Start reading today to unlock the potential of cloud-hosted artificial intelligence.