About Course

This one day instructor led course introduces participants to the big data capabilities of Google Cloud Through a combination of presentations demos and hands on labs participants get an overview of the Google Cloud and a detailed view of the data processing and machine learning capabilities This course showcases the ease flexibility and power of big data solutions on Google Cloud

Prerequisite Courses

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.

Skills Gained

This course teaches participants the following skills:

• Identify the purpose and value of the key Big Data and Machine Learning products on Google Cloud.
• Use Cloud SQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud.
• 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 Google Cloud.

Who Can Benefit

This class is intended for the following:

• Data analysts, Data scientists, Business analysts getting started with Google Cloud.
• 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 for use by data scientists.

Course Details

Course Outline

• Google Platform Fundamentals Overview.
• Google Cloud Platform Big Data Products.

Module 1: Introducing Google Cloud Platform

• CPUs on demand (Compute Engine).
• A global filesystem (Cloud Storage).
• CloudShell.
• Lab: Set up a Ingest-Transform-Publish data processing pipeline.

• Stepping-stones to the cloud.
• Cloud SQL: your SQL database on the cloud.
• Lab: Importing data into CloudSQL and running queries.
• Spark on Dataproc.
• Lab: Machine Learning Recommendations with Spark on Dataproc.