Professional Level
6 Hands-on labs

Google Cloud Certified Professional Data Engineer (LA)

By Matthew Ulasien

Learn how to master data and machine learning services on the Google Cloud Platform to become a certified Professional Data Engineer.

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20 hours
  • 80 Lessons
  • 6 Hands-On Labs
  • 6 Course Quizzes
  • 1 Practice Exam

About the course

The Google Cloud Professional Data Engineer is able to harness the power of Google’s big data capabilities and make data-driven decisions by collecting, transforming, and visualizing data. Through designing, building, maintaining, and troubleshooting data processing systems with a particular emphasis on the security, reliability, fault tolerance, scalability, fidelity, and efficiency of such systems, a Google Cloud data engineer is able to put these systems to work.

This course will prepare you for the Google Cloud Professional Data Engineer exam by diving into all of Google Cloud’s data services. With interactive demonstrations and an emphasis on hands-on work, you will learn how to master each of Google’s big data and machine learning services and become a certified data engineer on Google Cloud.

Updated to the latest Google exam requirements in July 2019, this course will prepare you to succeed in your quest to become Google Cloud Certified!

Lab Highlights

Create a Streaming Data Pipeline on GCP with Cloud Pub/Sub, Dataflow, and BigQuery Running a Pyspark Job on Cloud Dataproc Using Google Cloud Storage Exploring Cloud Firestore in Datastore Mode Managing Google Cloud SQL Instances Working with Data in Google Cloud SQL Setting Up for Google Cloud Spanner
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  • Chapter 1 7 Lessons Getting Started 22:16

    An Important Note About A Cloud Guru and Linux Academy Courses

    1:19

    Course Introduction

    5:48

    About the Training Architect

    0:41

    Course Updated for March 2019 Refresh

    1:09

    Intro to the Data Dossier - Interactive Study Guide

    4:53

    Course and Exam Overview

    5:06

    What is a Data Engineer

    3:20
  • Chapter 2 6 Lessons Foundational Concepts 1:07:51

    Data Lifecycle

    11:42

    Batch and Streaming Data

    5:28

    Cloud Storage as Staging Ground

    7:16

    Database Types

    7:21

    Monitoring Unmanaged Databases

    6:04

    Google Cloud Data Engineer - Foundational Concepts

    30:00 Quiz
  • Chapter 3 7 Lessons Cloud SQL 2:10:08

    Choosing a Managed Database

    7:15

    Cloud SQL Basics

    5:08

    Cloud SQL Hands On

    12:46

    Importing Data

    12:10

    SQL Query Best Practices

    2:49

    Managing Google Cloud SQL Instances

    1:00:00 Hands-On Lab

    Working with Data in Google Cloud SQL

    30:00 Hands-On Lab
  • Chapter 4 5 Lessons Datastore 1:13:13

    Datastore Overview

    9:21

    Data Organization

    16:03

    Queries and Indexing

    11:30

    Data Consistency

    6:19

    Exploring Cloud Firestore in Datastore Mode

    30:00 Hands-On Lab
  • Chapter 5 4 Lessons Bigtable 40:02

    Bigtable Overview

    7:44

    Instance Configuration

    18:12

    Data Organization

    5:29

    Schema Design

    8:37
  • Chapter 6 5 Lessons Cloud Spanner 1:30:15

    Cloud Spanner Overview

    11:17

    Data Organization and Schema

    7:12

    Hands On and Viewing Examples

    11:46

    QUIZ: Managed Databases on Google Cloud

    30:00 Quiz

    Setting Up for Google Cloud Spanner

    30:00 Hands-On Lab
  • Chapter 7 5 Lessons Real Time Messaging with Cloud Pub/Sub 54:02

    Streaming Data Challenges

    8:25

    Cloud Pub/Sub Overview

    12:29

    Pub/Sub Hands On

    18:24

    Connecting Kafka to GCP

    5:13

    Monitoring Subscriber Health

    9:31
  • Chapter 8 6 Lessons Data Pipelines with Cloud Dataflow 1:06:41

    Data Processing Pipelines

    5:24

    Cloud Dataflow Overview

    10:10

    Key Concepts

    9:43

    Template Hands On

    11:09

    Streaming Ingest Pipeline Hands On

    20:04

    Additional Best Practices

    10:11
  • Chapter 9 7 Lessons Dataproc 1:56:33

    Dataproc Overview

    10:49

    Configure Dataproc Cluster and Submit Job – Part 1

    15:36

    Configure Dataproc Cluster and Submit Job – Part 2

    14:36

    Migrating and Optimizing for Google Cloud

    9:50

    Best Practices for Cluster Performance

    5:42

    QUIZ: Data Ingest and Processing

    30:00 Quiz

    Run a Pyspark Job on Cloud Dataproc using Google Cloud Storage

    30:00 Hands-On Lab
  • Chapter 10 9 Lessons BigQuery 2:58:16

    BigQuery Overview

    14:44

    Interacting with BigQuery

    22:10

    Load and Export Data

    19:02

    Optimize for Performance and Costs

    15:30

    Streaming Insert Example

    8:39

    BigQuery Logging and Monitoring

    8:18

    BigQuery Best Practices

    14:53

    QUIZ: BIGQUERY

    30:00 Quiz

    Create Streaming Data Pipeline with Cloud Pub/Sub, Dataflow, and BigQuery

    45:00 Hands-On Lab
  • Chapter 11 3 Lessons Machine Learning 37:34

    What is Machine Learning?

    14:45

    Working with Neural Networks

    15:08

    Preventing Overfitted Training Data

    7:41
  • Chapter 12 4 Lessons AI Platform (Formerly Cloud ML Engine) 53:31

    GCP Machine Learning Services

    5:57

    AI Platform Overview

    16:52

    AI Platform Hands On Part 1

    15:04

    AI Platform Hands On Part 2

    15:38
  • Chapter 13 3 Lessons Pretrained Machine Learning API's 52:38

    Pre-trained ML API's

    9:10

    Vision API Demo

    13:28

    QUIZ: MACHINE LEARNING ON GOOGLE CLOUD

    30:00 Quiz
  • Chapter 14 2 Lessons Datalab 26:34

    Datalab Overview

    8:45

    Datalab Demo

    17:49
  • Chapter 15 4 Lessons Cleaning Your Data with Dataprep 51:35

    What is Dataprep?

    8:58

    Dataprep Demo Part 1

    14:16

    Dataprep Demo Part 2

    16:32

    Dataprep Demo Part 3

    11:49
  • Chapter 16 3 Lessons Building Data Visualizations with Data Studio 1:07:51

    Data Studio Introduction

    9:32

    Data Studio Demo

    28:19

    QUIZ: DATALAB/DATAPREP/DATA STUDIO

    30:00 Quiz
  • Chapter 17 2 Lessons Orchestrating Data Workflows with Cloud Composer 23:51

    Cloud Composer Overview

    8:26

    Hands On - Cloud Composer

    15:25
  • Chapter 18 5 Lessons Final Steps 2:12:36

    Additional Study Resources

    2:56

    Additional Hands On and Practice Resources

    4:43

    What's Next After Certification?

    3:42

    Keep Up to Date with GCP This Month

    1:15

    Data Engineer - Final Exam

    2:00:00 Quiz

What you will need

  • This is a challenging professional level exam. At a bare minimum, the following Linux Academy Courses (and certs) are highly recommended. - Google Cloud Essentials - Google Cloud Security Essentials - Google Cloud Certified Associate Cloud EngineerAdditionally, the exam will test technologies outside of Google Cloud services that we will cover but cannot provide an exhaustive deep dive such as: - SQL syntax - Machine Learning - Apache Beam - Hadoop ecosystem

What are Hands-on Labs

What's the difference between theoretical knowledge and real skills? Practical real-world experience. That's where Hands-on Labs come in! Hands-on Labs are guided, interactive experiences that help you learn and practice real-world scenarios in real cloud environments. Hands-on Labs are seamlessly integrated in courses, so you can learn by doing.

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