Google Cloud Platform Big Data & Machine Learning Fundamentals

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Duration: 1 Day
Training Fee: HK$6,500
Private in-house training
Apart from public, instructor-led classes, we also offer private in-house trainings for organizations based on their needs. Call us at +852 2116 3328 or email us at [email protected] for more details.
Course Objectives

This course teaches participants the following skills:

  • Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform.
  • Use Cloud SQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform.
  • Employ BigQuery and Cloud Datalab to carry out interactive data analysis.
  • Train and use a neural network using TensorFlow.
  • Employ ML APIs.
  • Choose between different data processing products on the Google Cloud Platform.

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

  • 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 Python.
  • Familiarity with machine learning and/or statistics.
Intended Audience

This class is intended for the following:

  • Data analysts, Data scientists, Business analysts getting started with Google Cloud Platform.
  • Individuals responsible for designing pipelines and architectures for data processing, creating and maintaining machine learning and statistical models, querying datasets, visualizing query results and creating reports.
  • Executives and IT decision makers evaluating Google Cloud Platform for use by data scientists.
Delivery Method
  • Instructor-led, instructor-led online
Course Outline

The course includes presentations, demonstrations, and hands-on labs.


Module 1: Introducing Google Cloud Platform
Module 2: Compute and Storage Fundamentals
Module 3: Data Analytics on the Cloud
Module 4: Scaling Data Analysis
Module 5: Machine Learning
Module 6: Data Processing Architectures
Module 7: Summary

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