Data Engineering and Automation with AI

Modern data engineering is evolving rapidly, and integrating artificial intelligence is no longer optional for building efficient data pipelines. This course teaches you how to leverage AI to automate data ingestion, transformation, and quality checks. You will learn how to write smarter code, design resilient workflows, and automate repetitive tasks using modern AI tools. By completing this text-only course, you will transform your approach to data management, moving from manual scripting to AI-driven automation. You will gain the confidence to design and maintain robust data architectures that leverage the latest technologies. What you'll learn: - Understand foundational data engineering concepts and modern pipeline architectures - Apply generative AI techniques to automate SQL query generation and Python scripting - Design automated data cleaning and transformation workflows with modern dataframe libraries - Configure AI-assisted data quality checks and validation rules to ensure data integrity - Implement basic orchestration patterns to automate pipeline execution schedules - Practice writing effective prompts specifically tailored for data engineering tasks This course begins with essential terminology and the core principles of data architecture, ensuring you have a solid foundation before moving on to practical automation techniques. You will read through step-by-step explanations, clear code examples, and structured scenarios designed to build your skills progressively. This course is designed for beginners who want to enter the data field, as well as data professionals looking to modernize their workflow with AI. No prior background in artificial intelligence or advanced programming is required. Start reading today to build smarter, faster, and more automated data pipelines.