Learn how to use Google BigQuery to enhance your data engineering and machine learning skills in this practical, instructor-led course. Taught by experienced cloud architect and author Dan Sullivan, you’ll work with BigQuery’s serverless architecture, advanced SQL, and data warehousing features to efficiently manage and analyze large datasets.



Google BigQuery for Data and ML Engineers

Instructor: Pearson
Access provided by Chandigarh University
Recommended experience
What you'll learn
Master BigQuery’s serverless architecture, data warehousing, and advanced SQL to efficiently manage and analyze large datasets.
Learn to build, evaluate, and deploy machine learning models directly within BigQuery, covering essential techniques.
Explore the cutting-edge applications of generative AI in BigQuery.
Skills you'll gain
Details to know

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8 assignments
September 2025
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There is 1 module in this course
This module provides a comprehensive overview of BigQuery for data engineering and machine learning. It covers BigQuery’s architecture, data ingestion (batch and streaming), data quality checks, and data exploration using SQL, Python, and Spark. The module then explores machine learning workflows, including classification, regression, and time series modeling directly in BigQuery. It concludes with practical applications of generative AI and text processing in BigQuery, featuring hands-on labs throughout to reinforce learning.
What's included
34 videos8 assignments
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