Data Engineering on Google Cloud

Get hands-on experience with designing and building data processing systems on Google Cloud. This course uses lectures, demos, and hands-on labs to show you how to design data processing systems, build end-to-end data pipelines, analyze data, and implement machine learning. This course covers structured, unstructured, and streaming data.                                                                  

Design and build data processing systems on Google Cloud.

• Process batch and streaming data by implementing autoscaling data pipelines on Dataflow.
• Derive business insights from extremely large datasets using BigQuery.
• Leverage unstructured data using Spark and ML APIs on Dataproc.
• Enable instant insights from streaming data.
• Understand ML APIs and BigQuery ML, and learn to use AutoML tocreate powerful models without coding.
• This course teaches participants the following skills:

Basic proficiency with a common query language such as SQL.

• Experience with data modeling and ETL (extract, transform, load) activities.
• Experience with developing applications using a common programming language such as Python.
• Familiarity with machine learning and/or statistics.
• To get the most of out of this course, participants should have:

Extracting, Loading, Transforming, cleaning, and validating data

• Designing pipelines and architectures for data processing
• Integrating analytics and machine learning capabilities into data pipelines
• Querying datasets, visualizing query results and creating reports
• This class is intended for developers who are responsible for: