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GenAI for Data Engineers: Scaling with GenAI

This course is part of Building Smarter Data Pipelines: SQL, Spark, Kafka & GenAI Specialization

Instructors: Christopher Klaus

Included with

Learn more

1 module

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

3 hours to complete

Flexible schedule

Learn at your own pace

1 module

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

3 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Identify the capabilities of GenAI for basic role specific, Data Engineer functions.
Examine real-world applications to leverage GenAI for streamlining work and fostering innovation in Data Engineering functions.
Deploy strategies and tactics to responsibly integrate GenAI into data engineering practices, while maintaining human oversight and accountability.

Skills you'll gain

Tools you'll learn

Generative AI

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

2 assignments¹

AI Graded see disclaimer

Taught in English

91%

of learners achieved a positive career outcome

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the Building Smarter Data Pipelines: SQL, Spark, Kafka & GenAI Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There is 1 module in this course

As part of the GenAI Academy, this course explores how Generative Artificial Intelligence (GenAI) is transforming the field of data engineering. This course serves as a primer where learners will discover the key capabilities of GenAI and uncover practical strategies to leverage these powerful tools in their day-to-day data engineering work.

This course is designed for data engineering team leaders and data engineers, including managers and team leads who are responsible for guiding their teams towards innovative practices, as well as data engineers and aspiring professionals looking to enhance their workflows and future-proof their skillsets by incorporating GenAI-powered tools. Learners should have a basic understanding of data pipelines, ETL/ELT processes, and data transformation, along with familiarity with databases, data warehouses, big data frameworks, and programming languages like Python and SQL. An open mindset and curiosity to explore new GenAI technologies are essential. By the end of this course, data engineers will be equipped with the knowledge and skills to start scaling their productivity by harnessing the transformative potential of GenAI.

Module details

This course serves as a primer where learners will discover the key capabilities of GenAI and uncover practical strategies to leverage these powerful tools in their day-to-day data engineering work. By the end of this course, data engineers will be equipped with the knowledge and skills to start scaling their productivity by harnessing the transformative potential of GenAI.

What's included

6 videos5 readings2 assignments1 peer review

6 videosTotal 50 minutes

Introduction to GenAI for Data Engineers4 minutes
History & Background for GenAI and Data Engineering9 minutes
Demo: Create Synthetic Data for Testing a Data Pipeline with ChatGPT6 minutes
Remediating Risks and Ethical Concerns7 minutes
Demo: Data Pipeline Development from Low-Code, to SQL, to Python with ChatGPT23 minutes
Closing Thoughts: What’s Next1 minute

5 readingsTotal 45 minutes

Our Roadmap & Resources Available: How to Get Started5 minutes
GenAI and Data Engineering: Glossary10 minutes
Demo: Create Synthetic Data for Testing a Data Pipeline with Google Gemini10 minutes
Demo: Create and Implement an Entity Relationship Diagram with CoPilot10 minutes
Demo: Data Pipeline Development with Data Loading and Code Documentation using ChatGPT10 minutes