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Google Cloud Platform: Data Engineering Certification Prep

The platform of choice of digital natives

Martijn van de Grift

Cloud is here to stay, and expertise with cloud technologies is in increasing demand. Google Cloud Data Engineers are some of the highest-paid in the industry today. This course will help you earn the GCP data engineering certification, an excellent way to advance your career by demonstrating proficiency to your employer or clients. By becoming Google Cloud Professional Data Engineer Certified, you show the world that you can design and build data processing systems and create machine learning models on Google Cloud Platform.

This course will cover all of the relevant topics for the exam, including Storage, big data processing, and machine learning.

What you'll learn-and how you can apply it

By the end of this live, hands-on, online course, you’ll understand:

  • How to build Big Data systems on Google Cloud, following industry best practices.
  • What kind of questions are asked on the exam and how to answer them.

And you will be able to:

  • Select and leverage the correct storage technologies on GCP
  • Design a data processing solution on GCP.
  • Design the best solution based on a customer case.
  • Leverage Google’s pre-built ML models.
  • Apply proven design patterns.
  • Take the Google Cloud Certified Professional Data Engineer exam.

This training course is for you because...

  • You want to get a really quick overview of data engineering on Google Cloud.
  • You already have some data engineering experience on Google Cloud, but you feel you’re not ready to take the exam.
  • You want to become a Google Cloud Certified Professional (Data Engineer).

Prerequisites

  • Good understanding of Computer Science, Software Engineering and Data Engineering.
  • Some prior experience with Google Cloud Platform and familiarity with GCP fundamentals, such as Cloud Networking, Regions, IAM, and monitoring and logging.
  • A high-level understanding of machine learning terminology.

Recommended preparation:

  • None

Recommended follow-up:

About your instructor

  • Martijn is a Cloud consultant at Binx.io, where he specializes in creating solutions using GCP and AWS. He holds most relevant technical certifications for both clouds. Martijn has a great passion for IT and likes to work with the latest technologies. He loves to share this passion during training, and webinars. He brings experience with handling planet-scale data from an assignment at Booking.com.

Schedule

The timeframes are only estimates and may vary according to how the class is progressing

Introduction (20 minutes)

  • Course overview
  • Presentation: Big data ecosystem, big data on Google Cloud, available services overview, accessing services, exam overview
  • Q&A

Storage (35 minutes)

  • Presentation: Cloud Storage, Cloud SQL & Spanner, BigTable, Datastore, BigQuery, data transfer, product selection
  • Q&A
  • Practice questions: Storage
  • Break (5 minutes)

Big Data Processing (30 minutes)

  • Presentation: Interactive vs. batch processing, Cloud Pub/Sub, Dataflow, Dataproc, Dataprep, product selection
  • Q&A
  • Practice questions: Big data processing

Machine Learning (30 minutes)

  • Presentation: Basics & terminology, Tensorflow, Cloud ML, Auto ML, AI Platform, product selection
  • Q&A
  • Practice questions: Machine Learning
  • Break (5 minutes)

Publishing and visualization datasets (20 minutes)

  • Presentation: BigQuery Views, Data Studio
  • Q&A
  • Practice questions: Publishing and visualizing data

Reference Architectures (20 minutes)

  • Presentation: Connecting services together by discussing Google advised architectures for Big data solutions.
  • Q&A

Practice exam questions (15 minutes)