April 2025
Intermediate
1h 50m
English
on-demand course
Solving Data Preparation Tasks with AI: From Data Engineering to Prompt Engineering
with Christian Koch, John Loutzenhiser
Closed Captioning available in German, English, Spanish, French, Italian, Japanese, Korean, Portuguese (Portugal, Brazil), Chinese (Simplified), Chinese (Traditional)
Overview
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.
What you’ll learn and how to apply it
- Become familiar with the fundamentals of AI in software and data engineering
- Use prompt engineering for:
- data collection
- data transformation
- data quality assurance and governance
- data integration
- Understand current trends and future perspectives in the area of prompt engineering
Prerequisites
- Basic understanding of the data science process
- Basic understanding of AI and ML
- Basic knowledge one IDE (Jupyter, PyCharm etc.)
- Python intermediate level
- Pandas intermediate level
Course Materials
The source code for course exercises can be found in the course GitHub repository
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