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Virtual Instructor-Led Training 

Free GCP Big Data and Machine Learning Fundamentals

September 14, 2023


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This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.


Date: September 14, 2023
Location: Online event
Time: 13:00 to 17:00 CET
Language: English

Who Should Attend

  • Data Analysts, Data Engineers, Data Scientists, and ML Engineers who are 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


  • Identify the data-to-AI lifecycle on Google Cloud and the major products of big data and machine learning.
  • Design streaming pipelines with Dataflow and Pub/Sub.
  • Analyze big data at scale with BigQuery.
  • Identify different options to build machine learning solutions on Google Cloud.
  • Describe a machine learning workflow and the key steps with Vertex AI.
  • Build a machine learning pipeline using AutoML.


This training is open to all.


This course is not associated with any Google Cloud certification, but attendees who successfully pass the Qwiklabs receive a certificate of attendance.

Course Outline

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

Module 1: Big Data and Machine Learning on Google Cloud

  • Identify the different aspects of Google Cloud’s infrastructure
  • Identify the big data and machine learning products on Google Cloud
Module 2: Data Engineering for Streaming Data
  • Describe an end-to-end streaming data workflow from ingestion to data visualization
  • Identify modern data pipeline challenges and how to solve them at scale with Dataflow
  • Build collaborative real-time dashboards with data visualization tools
Module 3: Big Data with BigQuery
  • Describe the essentials of BigQuery as a data warehouse
  • Explain how BigQuery processes queries and stores data
  • Define BigQuery ML project phases
  • Build a custom machine learning model with BigQuery ML
Module 4: Machine Learning Options on Google Cloud

  • Identify different options to build ML models on Google Cloud
  • Define Vertex AI and its major features and benefits
  • Describe AI solutions in both horizontal and vertical markets
Module 5: The Machine Learning Workflow with Vertex AI
  • Describe a ML workflow and the key steps
  • Identify the tools and products to support each stage
  • Build an end-to-end ML workflow using AutoML
Module 6: Summary
  • Recap of key learning points
  • Resources


Trainer Thomas van Latum 

Thomas van Latum is a Google Cloud Platform Authorized Trainer 

Register for the Core Infrastructure Training (September 14, 2023)