Introduction to Data Engineering using Generative AI

About this course

Updated description 3/12/2024Generative AI tools such as ChatGPT, Claude, and Bard are making data engineering more accessible and more efficient. If you work with spreadsheets or business intelligence tools but aren't too familiar with Python or SQL, then generative AI can help you analyze data and build your own data pipelines and ETL/ELT processes.

Generative AI and LLMs will not replace data engineers or data analysts but those who know how to use these AI tools will be able to build more capable and reliable data pipelines faster. They will also have access to a tool that can help you develop your Python, SQL, and data modeling skills by providing a variety of examples of functional code and help with error messages and troubleshooting processes that do not work as expected.

Learn Data Engineering Techniques as Well as Data Engineering Tools

In this course, you will learn how to break down data engineering problems into a series of tasks that can be automated using Python, SQL, and command line scripts generated by a large language model (LLM). Prompting an AI to "generate a data processing script to do X, Y, and Z" will probably not get you the results you expect. LLMs are powerful tools, but they are not oracles. As with any tool, we need to understand what the tool is capable of and how to use the capabilities to meet our needs. This course shows you how to think through a data transformation and loading problems, incrementally building components of a solution. This course is organized into several topics that cover the fundamental skills needed to begin work in data engineering using GenAI, including:

• Introduction to large language models, foundation models, and other AI topics related to data engineering.

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