AI and Machine Learning Fundamentals on Cloud Platforms

Cloud computing has revolutionized how we build and scale artificial intelligence, making powerful machine learning models accessible to everyone. If you want to understand how to leverage cloud-based AI tools to solve real-world problems, starting with the right foundation is essential. In this text-based course, you will transition from a beginner to a confident practitioner capable of navigating the entire data-to-AI lifecycle. You will explore how to manage datasets, train predictive models, and deploy modern generative AI solutions using cloud services. What you'll learn: Understand foundational AI and machine learning concepts, terminology, and cloud architectures; Explore the end-to-end data-to-AI lifecycle, from data preparation to model deployment; Compare predictive machine learning models with modern generative AI and large language models; Learn how to leverage cloud-based autoML and custom training pipelines for various business use cases; Discover best practices for responsible AI development, prompt engineering basics, and model evaluation. The course begins with core definitions and cloud infrastructure basics before guiding you through data preparation, model training, and deployment strategies. Through clear written explanations and conceptual walkthroughs, you will gain a practical framework for cloud-based AI development. This course is designed for aspiring data scientists, developers, and tech enthusiasts who are new to AI on the cloud. No prior machine learning or cloud engineering experience is required. Start your journey into cloud-based artificial intelligence today.