Cloud Data Engineering and Machine Learning Fundamentals

Modern businesses rely on data to drive key decisions, but managing massive datasets and extracting predictive insights requires a structured approach. This course provides a clear pathway to understanding how data engineering and machine learning work together in the cloud. You will transition from understanding basic data concepts to designing robust pipelines and integrating machine learning workflows. By reading through real-world scenarios and structured explanations, you will gain the confidence to process big data and support intelligent decision-making systems. What you'll learn: - Understand foundational cloud data architecture, storage options, and database types - Design streaming and batch data pipelines using managed cloud services - Query and analyze massive datasets efficiently using serverless data warehouses - Apply machine learning concepts to preprocess data and train predictive models - Explore modern data patterns including lakehouse architectures and vector search integrations - Implement best practices for data security, pipeline monitoring, and governance The journey begins with core data concepts and storage foundations before moving into pipeline construction and analytical processing. You will then progress to machine learning fundamentals, exploring how to clean data, train models, and leverage modern AI patterns. This course is designed for beginners, aspiring data engineers, and business analysts who want to build a strong foundation in cloud-based data systems with no prior cloud experience required. Start your journey into the world of cloud data and machine learning today.