GCP Big Data & ML fundamentals training 7 April 2022

7 April 2022 | 9:00 – 17:00

Get started with Big Data and Machine Learning on GCP.

The training offers a combination of presentations, demos, and hands-on labs that introduce you to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). You will learn to process Big Data at scale for analytics and Machine Learning. You will explore the fundamentals of building new machine learning models and creating streaming data pipelines and dashboards.

The training on April 7th will run from 9:00 – 17:00 CET (3 am EST – 11 am EST / 12:30 pm – 8:30 pm IST). During the training, you will go hands-on with several Qwiklabs.

Through a combination of presentations, demos, and hands-on labs, experienced trainer Martijn van de Grift will discuss the value of Google Cloud Platform for big data and ML solutions.

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What to Expect

Google Cloud Big Data and Machine Learning Fundamentals Is Perfect for

Data Engineers, Data Scientists, Tech Leads, Solution Engineers and Data Analysts. Before enrolling in this course, you should have a year of experience with one or more of the following: A common query language like SQL Extract, transform, load activities Data modeling Machine learning and/or statistics Programming in Python.

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

Module 1: Introducing Google Cloud Platform

Google Platform Fundamentals Overview.
Google Cloud Platform Big Data Products.
Lab: Sign up for Google Cloud Platform.

Module 2: Compute and Storage Fundamentals

CPUs on demand (Compute Engine).
A global file system (Cloud Storage).
Cloud Shell.
Lab: Set up an 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 a 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.

About the Trainer

Martijn van de Grift is a cloud consultant at Binx.io who obtained a wide variety of technical AWS & GCP certifications. He loves to share this passion during training sessions and webinars.

Not only is Martijn an Authorized Instructor for both Amazon Web Services and Google Cloud Platform, but he is also an official trainer with IT publisher O’Reilly and a guest lecturer at the Amsterdam University of Applied Sciences.