Google Cloud Platform Big Data and Machine Learning Fundamentals
At the end of this course, participants will be able to:
• Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform
• Use CloudSQL 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
• Choose between Cloud SQL, BigTable and Datastore
• Train and use a neural network using TensorFlow
• Choose between different data processing products on the Google Cloud Platform
Before enrolling in this course, participants should have roughly one (1) year of experience with one or more of the following:
• A common query language such as SQL
• Extract, transform, load activities
• Data modeling
• Machine learning and/or statistics
• Programming in Python
Google Account Notes:
• You’ll need a Google/Gmail account and a credit card or bank account to sign up for the Google Cloud Platform free trial (Google is currently blocked in China).
• There is a known issue with certain EU countries where individuals are not able to sign up, but you may sign up as “business” status and intend to see a potential economic benefit from the trial. More details at: https://support.google.com/cloud/answer/6090602
• More Google Cloud Platform free trial FAQs are available at: https://cloud.google.com/free-trial/
Introduction to the Data and Machine Learning on Google Cloud Platform Specialization
Module 1: Introduction to Google Cloud Platform and its Big Data Products
In this module you will be introduced to Google Cloud Platform and the data handling aspects of the platform.
Module 2: Foundations of GCP Compute and Storage
In this module, we introduce the foundations of the Google Cloud Platform: compute and storage and introduce how they work to provide data ingest, storage, and federated analysis.
Module 3: Data Analysis on the Cloud
In this module we introduce the common Big Data use cases that Google will manage for you. These are the things that are widely done in industry today and for which we provide easy migration to the cloud.
Module 4: Scaling Data Analysis: Compute with GCP
This module is about the more transformational technologies in Google Cloud platform that may not have immediate parallels to technologies that attendees are using (“what’s next”).
Module 5: Data Processing Architectures: Scalable Ingest, Transform and Load
In this module we will introduce you to data processing architectures in Google Cloud Platform: Asynchronous processing with TaskQueues. Message-oriented architectures with Pub/Sub. Creating pipelines with Dataflow.
Module 6: Summary of Google Cloud Platform, Big Data, and ML
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