My Account Log in

1 option

Solving data preparation tasks with AI : from data engineering to prompt engineering.

O'Reilly Online Learning: Academic/Public Library Edition Available online

View online
Format:
Video
Contributor:
Koch, Christian, instructor.
Loutzenhiser, John, instructor.
O'Reilly (Firm), publisher.
Language:
English
Subjects (All):
Artificial intelligence.
Electronic data processing--Data preparation.
Electronic data processing.
Physical Description:
1 online resource (1 video file (1 hr., 51 min.)) : sound, color.
Edition:
[First edition].
Place of Publication:
[Sebastopol, California] : O'Reilly Media, Inc., [2025]
Summary:
In this course, you will learn the practical skills needed to harness AI effectively in data engineering. Each lesson guides you through the intricate process of crafting prompts tailored to various stages of data preparation. You’ll explore the art of creating prompts for data collection, data transformation, data quality assurance and governance, and data integration. This course walks you through the full data engineering lifecycle. You'll learn how to construct prompts that facilitate the transformation of raw data into meaningful insights, enabling effective decision-making processes. You'll discover strategies for crafting prompts that uphold data integrity, ensuring that your data-driven initiatives are built on a foundation of trust and reliability. You'll master the art of creating prompts that streamline the integration process, paving the way for comprehensive data analysis and interpretation. Finally, we'll take a brief look at current trends and future perspectives in AI and data engineering. You’ll discover valuable insights into emerging technologies and industry developments, empowering you to stay ahead in this rapidly evolving field. By the end of this course, you'll not only grasp the fundamental principles of AI in data engineering but also possess the practical skills needed to leverage AI effectively in real-world scenarios, making you a valuable asset in today's data-driven landscape.
Notes:
OCLC-licensed vendor bibliographic record.
OCLC:
1519554465
Publisher Number:
0642572055905

The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.

Find

Home Release notes

My Account

Shelf Request an item Bookmarks Fines and fees Settings

Guides

Using the Find catalog Using Articles+ Using your account