Udemy
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
Development
Web Development Data Science Mobile Development Programming Languages Game Development Database Design & Development Software Testing Software Engineering Development Tools No-Code Development
Business
Entrepreneurship Communications Management Sales Business Strategy Operations Project Management Business Law Business Analytics & Intelligence Human Resources Industry E-Commerce Media Real Estate Other Business
Finance & Accounting
Accounting & Bookkeeping Compliance Cryptocurrency & Blockchain Economics Finance Finance Cert & Exam Prep Financial Modeling & Analysis Investing & Trading Money Management Tools Taxes Other Finance & Accounting
IT & Software
IT Certification Network & Security Hardware Operating Systems Other IT & Software
Office Productivity
Microsoft Apple Google SAP Oracle Other Office Productivity
Personal Development
Personal Transformation Personal Productivity Leadership Career Development Parenting & Relationships Happiness Esoteric Practices Religion & Spirituality Personal Brand Building Creativity Influence Self Esteem & Confidence Stress Management Memory & Study Skills Motivation Other Personal Development
Design
Web Design Graphic Design & Illustration Design Tools User Experience Design Game Design Design Thinking 3D & Animation Fashion Design Architectural Design Interior Design Other Design
Marketing
Digital Marketing Search Engine Optimization Social Media Marketing Branding Marketing Fundamentals Marketing Analytics & Automation Public Relations Advertising Video & Mobile Marketing Content Marketing Growth Hacking Affiliate Marketing Product Marketing Other Marketing
Lifestyle
Arts & Crafts Beauty & Makeup Esoteric Practices Food & Beverage Gaming Home Improvement Pet Care & Training Travel Other Lifestyle
Photography & Video
Digital Photography Photography Portrait Photography Photography Tools Commercial Photography Video Design Other Photography & Video
Health & Fitness
Fitness General Health Sports Nutrition Yoga Mental Health Dieting Self Defense Safety & First Aid Dance Meditation Other Health & Fitness
Music
Instruments Music Production Music Fundamentals Vocal Music Techniques Music Software Other Music
Teaching & Academics
Engineering Humanities Math Science Online Education Social Science Language Teacher Training Test Prep Other Teaching & Academics
AWS Certification Microsoft Certification AWS Certified Solutions Architect - Associate AWS Certified Cloud Practitioner CompTIA A+ Cisco CCNA CompTIA Security+ Amazon AWS Microsoft AZ-900
Graphic Design Photoshop Adobe Illustrator Drawing Digital Painting InDesign Character Design Canva Figure Drawing
Life Coach Training Neuro-Linguistic Programming Personal Development Personal Transformation Mindfulness Life Purpose Meditation CBT Emotional Intelligence
Web Development JavaScript React CSS Angular PHP Node.Js WordPress Vue JS
Google Flutter Android Development iOS Development React Native Swift Dart (Programming Language) Mobile Development Kotlin SwiftUI
Digital Marketing Google Ads (Adwords) Social Media Marketing Google Ads (AdWords) Certification Marketing Strategy Internet Marketing YouTube Marketing Email Marketing Retargeting
Microsoft Power BI SQL Tableau Business Analysis Data Modeling Business Intelligence MySQL Data Analysis Blockchain
Business Fundamentals Entrepreneurship Fundamentals Business Strategy Business Plan Startup Freelancing Online Business Blogging Home Business
Unity Game Development Fundamentals Unreal Engine C# 3D Game Development C++ 2D Game Development Unreal Engine Blueprints Blender
30-Day Money-Back Guarantee
IT & Software IT Certification Google Cloud Professional Data Engineer

Google Cloud Professional Data Engineer: Get Certified 2020

Build scalable, reliable data pipelines, databases, and machine learning applications.
Bestseller
Rating: 4.4 out of 54.4 (892 ratings)
27,692 students
Created by Dan Sullivan
Last updated 11/2020
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • How to pass the Google Cloud Professional Data Engineer Exam
  • Build scalable, reliable data pipelines
  • Choose appropriate storage systems, including relational, NoSQL and analytical databases
  • Apply multiple types of machine learning techniques to different use cases
  • Deploy machine learning models in production
  • Monitor data pipelines and machine learning models
  • Design scalable, resilient distributed data intensive applications
  • Migrate data warehouse from on-premises to Google Cloud
  • Evaluate and improve the quality of machine learning models
  • Grasp fundamental concepts in machine learning, such as backpropagation, feature engineering, overfitting and underfitting.
Curated for the Udemy for Business collection

Requirements

  • Understanding of basic cloud computing concepts such as virtual machines and databases.
  • One year or more experience working with data management or data analysis

Description

The need for data engineers is constantly growing and certified data engineers are some of the top paid certified professionals. Data engineers have a wide range of skills including the ability to design systems to ingest large volumes of data, store data cost-effectively, and efficiently process and analyze data with tools ranging from reporting and visualization to machine learning. Earning a Google Cloud Professional Data Engineer certification demonstrates you have the knowledge and skills to build, tune, and monitor high performance data engineering systems.

This course is designed and developed by the author of the official Google Cloud Professional Data Engineer exam guide and a data architect with over 20 years of experience in databases, data architecture, and machine learning. This course combines lectures with quizzes and hands-on practical sessions to ensure you understand how to ingest data, create a data processing pipelines in Cloud Dataflow, deploy relational databases, design highly performant Bigtable, BigQuery, and Cloud Spanner databases, query Firestore databases, and create a Spark and Hadoop cluster using Cloud Dataproc.

The final portion of the course is dedicated to the most challenging part of the exam: machine learning.  If you are not familiar with concepts like backpropagation, stochastic gradient descent, overfitting, underfitting, and feature engineering then you are not ready to take the exam. Fortunately, this course is designed for you. In this course we start from the beginning with machine learning, introducing basic concepts, like the difference between supervised and unsupervised learning. We’ll build on the basics to understand how to design, train, and evaluate machine learning models. In the process, we’ll explain essential concepts you will need to understand to pass the Professional Data Engineer exam. We'll also review Google Cloud machine learning services and infrastructure, such as BigQuery ML and tensor processing units.

The course includes a 50 question practice exam that will test your knowledge of data engineering concepts and help you identify areas you may need to study more.

By the end of this course, you will be ready to use Google Cloud Data Engineering services to design, deploy and monitor data pipelines, deploy advanced database systems, build data analysis platforms, and support production machine learning environments.


ARE YOU READY TO PASS THE EXAM? Join me and I'll show you how!

Who this course is for:

  • Cloud engineers and architects who want to pass the Professional Data Engineer exam
  • Data engineers who want to learn about Google's advanced tools and services for data engineering
  • Data scientists and data engineers who want to understand machine learning concepts
  • Cloud application developers who want to use machine learning to build applications
  • Devops engineers who need to support data engineering pipelines and machine learning models

Course content

22 sections • 110 lectures • 5h 48m total length

  • Preview02:12
  • Preparing for the Google Cloud Professional Data Engineer Exam
    03:27

  • Preview07:13
  • Preview03:45
  • Access Controls for Cloud Storage
    02:15
  • Lifecycle Policy Management
    02:26
  • Using Cloud Storage Console
    05:16
  • Exercise: Cloud Storage
    00:13
  • Solution: Cloud Storage
    01:39

  • Introduction to Relational Databases
    07:56
  • When to use Cloud SQL
    02:30
  • Creating a Cloud SQL Database
    05:00
  • Monitoring Cloud SQL
    02:12
  • Exercise: Create a Cloud SQL Database
    00:31
  • Solution: Create a Cloud SQL Database
    02:32

  • When to use Cloud Spanner
    01:35
  • Creating a Cloud Spanner Database
    03:57
  • Preview03:31
  • Check Your Knowledge: Choosing a Primary Key for a Spanner Table
    1 question

  • Introduction to Cloud Firestore & Document Databases
    03:01
  • Entities and Kinds
    02:01
  • Indexing in Cloud Firestore
    01:47
  • Creating Entities
    03:55
  • Querying Entities
    02:48
  • Creating Kinds and Namespaces
    02:26
  • Working with Transactions
    01:58
  • Exercise: Create a Kind and Entities
    00:27
  • Solution: Creating Kinds and Entities
    01:22

  • Introduction to Bigtable and Wide-Column Databases
    04:32
  • Creating a Bigtable Instance
    03:11
  • Designing Row-keys for Bigtable
    05:32
  • Query Patterns and Denormalization
    04:01
  • Designing for Time Series Data
    04:48
  • Check Your Knowledge: Creating a Time Series Database
    1 question

  • Introduction to BigQuery and Analytical Databases
    05:18
  • BigQuery Scalar Datatypes
    01:09
  • BigQuery Nested and Repeated Fields
    01:28
  • Preview04:31
  • Exercise: Querying BigQuery Public Datasets
    00:27
  • Solution: Querying BigQuery Public Datasets
    00:59
  • Access Controls in BigQuery
    01:15
  • Partitioning Tables
    04:43
  • Clustering Partitioned Tables
    01:06
  • Loading Data into BigQuery
    02:48

  • Assessing the Current State of a Data Warehouse
    03:19
  • Schema and Data Transfer
    03:06
  • Data Pipelines
    01:57
  • Reporting and Analysis
    01:45
  • Data Governance
    02:20
  • Check Your Knowledge: Data Warehouse Migration
    1 question

  • Using Caching to Improve Performance
    04:28
  • Cloud Memorystore Data Structures
    02:02
  • When to use Cloud Memorystore
    04:01
  • Check Your Knowledge: Redesign a Distributed Application for High Availability
    1 question

  • Introduction to Cloud Composer
    03:23
  • Cloud Composer Architecture
    03:17
  • Introduction to Cloud Data Fusion
    03:20

Instructor

Dan Sullivan
Architect and Author
Dan Sullivan
  • 4.5 Instructor Rating
  • 5,579 Reviews
  • 75,930 Students
  • 4 Courses

Dan Sullivan is a cloud architect, systems developer, and author of the Official Google Cloud Professional Data Engineer Study Guide. He is an experienced trainer and his online training courses have been viewed over 1 million times. Dan has extensive experience in multiple fields, including cloud architecture,  data architecture and modeling, machine learning, data science, and streaming analytics.

Dan is also the author of the Official Google Cloud Professional Architect Study Guide, Official Google Cloud Associate Engineer Study Guide, and NoSQL for Mere Mortals.

  • Udemy for Business
  • Teach on Udemy
  • Get the app
  • About us
  • Contact us
  • Careers
  • Blog
  • Help and Support
  • Affiliate
  • Impressum Kontakt
  • Terms
  • Privacy policy
  • Cookie settings
  • Sitemap
  • Featured courses
Udemy
© 2021 Udemy, Inc.