Google Cloud Big Data and Machine Learning Fundamentals

  • Tuition USD $675 GSA  $471.03
  • Reviews star_rate star_rate star_rate star_rate star_half 1131 Ratings
  • Course Code GCP-BD-ML
  • Duration 1 day
  • Available Formats Classroom, Virtual

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.

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.

Prerequisites

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.

Course Details

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

Course Outline

Module 1: Introducing Google Cloud Platform

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

Module 2: Compute and Storage Fundamentals

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

Module 3: Data Analytics on the Cloud

  • 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.

Module 4: Scaling Data Analysis

  • Fast random access.
  • Datalab.
  • BigQuery.
  • Lab: Build machine learning dataset.

Module 5: Machine Learning

  • Machine Learning with TensorFlow.
  • Lab: Carry out ML with TensorFlow
  • Pre-built models for common needs.
  • Lab: Employ ML APIs.

Module 6: Data Processing Architectures

  • Message-oriented architectures with Pub/Sub.
  • Creating pipelines with Dataflow.
  • Reference architecture for real-time and batch data processing.

Module 7: Summary

  • Why GCP?
  • Where to go from here
  • Additional Resources

When does class start/end?

Classes begin promptly at 9:00 am, and typically end at 5:00 pm.

Does the course schedule include a Lunchbreak?

Lunch is normally an hour long and begins at noon. Coffee, tea, hot chocolate and juice are available all day in the kitchen. Fruit, muffins and bagels are served each morning. There are numerous restaurants near each of our centers, and some popular ones are indicated on the Area Map in the Student Welcome Handbooks - these can be picked up in the lobby or requested from one of our ExitCertified staff.

How can someone reach me during class?

If someone should need to contact you while you are in class, please have them call the center telephone number and leave a message with the receptionist.

What languages are used to deliver training?

Most courses are conducted in English, unless otherwise specified. Some courses will have the word "FRENCH" marked in red beside the scheduled date(s) indicating the language of instruction.

What does GTR stand for?

GTR stands for Guaranteed to Run; if you see a course with this status, it means this event is confirmed to run. View our GTR page to see our full list of Guaranteed to Run courses.

Does ExitCertified deliver group training?

Yes, we provide training for groups, individuals and private on sites. View our group training page for more information.

Does ExitCertified deliver group training?

Yes, we provide training for groups, individuals, and private on sites. View our group training page for more information.

I took the AWS Technical Essentials and it was taught very well. It was very comprehensive and the instructor was fantastic. Already having familiarity with AWS, it was still taught at a level where I felt like it was worth taking before doing taking the AWS Developer course.

It was a pleasant experience from registration all through the course. I just wish they would have covered 100% of the material covered by the exam.

Pretty concise course mainly covering AWS Redshift while briefly introducing practical use examples with other services for companies.

I really enjoy the subject matter presented in this course. The instructor was very well verse and presented the material in a easy to understand and professional way... Great job!

Well organized, but the training should have included lab times as well, labs won't be done during breaks.

2 options available

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  • Feb 1, 2021 Feb 1, 2021 (1 day)
    Location
    iMVP
    Language
    English
    Time
    9:00AM 5:00PM CST
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  • Jun 14, 2021 Jun 14, 2021 (1 day)
    Location
    iMVP
    Language
    English
    Time
    9:00AM 5:00PM CDT
    Enroll
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