Google Cloud Big Data and Machine Learning Fundamentals

Description

Google Cloud Big Data and Machine Learning Fundamentals introduces participants to the capabilities of Google Cloud Platform. 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.

Who can benefit?

• 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

Prerequisites

• 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

What you’ll learn

• 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

Course Outline

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

For more information about Google’s Big Data, please check this page, as well as P2L‘s blog.