Data Engineering Essentials is tailored for aspiring data engineers and scientists interested in the architectural aspects of data handling and the technical skills necessary for managing large datasets efficiently. This course covers data engineering foundations, including data storage solutions, APIs, and data ingestion techniques. Participants will also learn to build and automate ETL (Extract, Transform, Load) pipelines and ensure data quality. Additionally, the course provides an introduction to big data tools like Hadoop and Spark, and explores cloud data services from providers such as AWS, GCP, and Azure. The capstone project at the end allows students to apply their skills in a real-world scenario, encompassing project planning, execution, and presentation of results. This course prepares learners to design and manage scalable data infrastructures, crucial for today’s data-driven decision-making environments.