Training offering

Google Cloud Platform Big Data and Machine Learning Fundamentals

Information

Price £595 before tax
Length: 1 Day
Course code: GOG_GCP-BD
Delivery Type

Session dates

This training is also available as onsite training. Feel free to contact us for more information.

Description

This one-day instructor-led course introduces participants to the big data capabilities of Google Cloud Platform. Through a combination of presentations, demos, and hands-on labs, you will get an overview of the Google Cloud platform 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 Platform.


Objectives



  • Purpose and value of the key Big Data and Machine Learning products in the GoogleCloud Platform




  • Use Cloud SQL and Cloud Dataproc to migrate existing MySQL andHadoop/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




Participants



  • Data analysts getting started with Google Cloud Platform




  • Data scientists getting started with Google Cloud Platform




  • 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




Prerequisite(s)



  • 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




Programme

1. Introducing Google Cloud Platform





  • Google Platform Fundamentals Overview




  • Google Cloud Platform Data Products and Technology




  • Usage scenarios





 



2. Compute and Storage Fundamentals





  • CPUs on demand (Compute Engine)




  • A global filesystem (Cloud Storage)




  • CloudShell





 



3. Data Analytics on the Cloud





  • Stepping-stones to the cloud




  • CloudSQL: your SQL database on the cloud




  • Lab: Importing data into CloudSQL and running queries




  • Spark on Dataproc





 



4. Scaling Data Analysis





  • Fast random access




  • Datalab




  • BigQuery




  • Machine Learning with TensorFlow




  • Fully built models for common needs





 



5. Data Processing Architectures





  • Message-oriented architectures with Pub/Sub




  • Creating pipelines with Dataflow




  • Reference architecture for real-time and batch data processing





 



6. Summary





  • Why GCP?




  • Where to go from here




  • Additional Resources





Classroom Live Labs



Lab 1: Sign up for Google Cloud Platform



Lab 2: Set up a Ingest-Transform-Publish data processing pipeline



Lab 3: Machine Learning Recommendations with SparkML



Lab 4: Build machine learning dataset



Lab 5: Train and use neural network



Lab 6: Employ ML APIs


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