Overview

Data Engineers design solutions that ensure maximum flexibility and scalability, while meeting all required security controls.

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

This Google Cloud course covers structured, unstructured, and streaming data.

Skills Covered

  • Design and build data processing systems on Google Cloud Platform.
  • Leverage unstructured data using Spark and ML APIs on Cloud Dataproc.
  • Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow.
  • Derive business insights from extremely large datasets using Google BigQuery.
  • Train, evaluate and predict using machine learning models using TensorFlow and Cloud ML.
  • Enable instant insights from streaming data

Who Should Attend

This class is intended for experienced developers who are responsible for managing big data transformations including:

  • Extracting, loading, transforming, cleaning, and validating data.
  • Designing pipelines and architectures for data processing.
  • Creating and maintaining machine learning and statistical models.
  • Querying datasets, visualizing query results and creating reports

Course Curriculum

Prerequisites

To get the most of out of this course, participants should have:

  • Completed Google Cloud Fundamentals – Big Data and Machine Learning course OR have equivalent experience.
  • Basic proficiency with common query language such as SQL Experience with data modeling, extract, transform, load activities.
  • Developing applications using a common programming language such as Python Familiarity with basic statistics

 

Download Syllabus