Data Engineering with Command Line Tools and Web Applications

Modern data engineering requires more than just moving data; it requires building robust, portable tools that automate complex tasks and serve models efficiently. This course provides the essential skills to bridge the gap between raw data and functional applications. You will transition from writing simple scripts to developing professional-grade command-line tools and microservices that integrate seamlessly into any data pipeline. By the end of this course, you will be able to create, deploy, and maintain the software components that power modern data infrastructure. What you'll learn: - Build efficient command-line interface (CLI) tools using Python and Bash to automate data processing. - Develop and deploy microservices using modern web frameworks to create portable data solutions. - Leverage Jupyter notebooks for interactive data exploration and machine learning model deployment. - Apply SQL and Python techniques to manage and query data across distributed environments. - Implement modern Python features like type hints to create more reliable and maintainable data applications. - Understand the basics of containerization to ensure your data tools run consistently in any environment. The course begins with foundational definitions and key terminology before moving into practical command-line automation and the structured development of web-based data applications. You will read through detailed explanations and apply your knowledge through written exercises designed to simulate real-world data engineering scenarios. This course is designed for beginners and aspiring data engineers who want to move beyond basic scripting into building production-ready tools. No prior experience with web development or advanced DevOps is required. Start building professional data engineering applications today.