Training schedule


Contact Giovanni Lanzani, if you want to know more about custom data & AI training for your teams. He’ll be happy to help you!
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This one-day instructor-led Google Cloud Platform 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.

This training is for you if…

you 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

This training is not for you if…

you have:

  • No experience with common query language
  • No familiarity with Machine Learning
  • No experience with data modelling

Clients we've helped

What you'll learn

  • 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

The schedule

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

  • Train and use a neural network using TensorFlow
  • Employ ML APIs
  • Choose between different data processing products on the Google Cloud Platform

Get In Touch!

Contact Max Driessen now if you want to learn more and take your cloud skills to the next level!

meet your trainer

Koen Maes


Koen is a very experienced consultant with a long history in the information technology and services industry. He takes on a wide variety of roles in software development, always evolving and keeping up with new innovations. He picked up the potential of the cloud early on, which led him to become one of the first Authorized Trainers for Google Cloud.

He’s passionate about creating value for the customer… and getting things done!

Flexible delivery

The Right Format For Your Preferred Learning Style

In-Classroom & In-Company Training
Online, Instructor-Led Training
Hybrid and Blended Learning
Self-Paced Training
Get in touch with the experts

Have any questions?

Contact Giovanni Lanzani, our Managing Director of Learning and Development, if you want to know more. He’ll be happy to help you!

Call me back

You can reach him out by phone as well at +31 6 51 20 6163

Course: Google Cloud Big Data and ML Fundamentals

Book now