AI and Machine Learning on Cloud Platform: Foundations and Solutions

Organizations are increasingly leveraging cloud infrastructure to scale their artificial intelligence and machine learning initiatives. This course provides a comprehensive introduction to the tools and workflows required to transition from raw data to intelligent, deployed solutions. You will gain a clear understanding of how to manage the end-to-end development process, moving from initial data ingestion to model deployment and monitoring. By focusing on modern cloud-based workflows, you will learn how to select the right tools for specific business goals and technical requirements. What you'll learn: - Understand the core concepts of the data-to-AI lifecycle and cloud-based development. - Explore specialized tools for building, training, and deploying machine learning models. - Configure automated ML pipelines to streamline the transition from experimentation to production. - Apply generative AI patterns including prompt engineering and foundation model tuning. - Master the fundamentals of model monitoring and basic MLOps to ensure long-term performance. - Practice defining AI solutions for various professional roles, from data science to engineering.\n The course begins with foundational definitions and terminology before moving into structured explanations of practical workflows for developers and analysts. You will read through detailed modules that cover both traditional machine learning and modern generative AI approaches. This course is designed for beginners interested in cloud-based AI, with no prior experience in machine learning or cloud architecture required. Start your journey into cloud-driven intelligence today.