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Professional Data Engineer: Professional Data Engineer on Google Cloud Platform Certification Video Training Course

The complete solution to prepare for for your exam with Professional Data Engineer: Professional Data Engineer on Google Cloud Platform certification video training course. The Professional Data Engineer: Professional Data Engineer on Google Cloud Platform certification video training course contains a complete set of videos that will provide you with thorough knowledge to understand the key concepts. Top notch prep including Google Professional Data Engineer exam dumps, study guide & practice test questions and answers.

115 Students Enrolled
201 Lectures
03:47:10 Hours

Professional Data Engineer: Professional Data Engineer on Google Cloud Platform Certification Video Training Course Exam Curriculum

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1

You, This Course and Us

1 Lectures
Time 00:02:01
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2

Introduction

3 Lectures
Time 00:23:26
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3

Compute

13 Lectures
Time 01:32:14
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4

Storage

12 Lectures
Time 01:32:13
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5

Cloud SQL, Cloud Spanner ~ OLTP ~ RDBMS

7 Lectures
Time 00:54:46
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6

BigTable ~ HBase = Columnar Store

6 Lectures
Time 00:54:18
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7

Datastore ~ Document Database

2 Lectures
Time 00:20:52
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8

BigQuery ~ Hive ~ OLAP

11 Lectures
Time 01:30:56
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9

Dataflow ~ Apache Beam

10 Lectures
Time 01:35:33
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10

Dataproc ~ Managed Hadoop

7 Lectures
Time 00:51:56
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11

Pub/Sub for Streaming

9 Lectures
Time 01:03:22
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12

Datalab ~ Jupyter

4 Lectures
Time 00:25:58
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13

TensorFlow and Machine Learning

27 Lectures
Time 03:49:01
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14

Regression in TensorFlow

16 Lectures
Time 02:25:49
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15

Vision, Translate, NLP and Speech: Trained ML APIs

4 Lectures
Time 00:43:52
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16

Virtual Machines and Images

7 Lectures
Time 00:46:24
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17

VPCs and Interconnecting Networks

19 Lectures
Time 03:07:31
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18

Managed Instance Groups and Load Balancing

14 Lectures
Time 01:56:23
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19

Ops and Security

12 Lectures
Time 01:39:51
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20

Appendix: Hadoop Ecosystem

17 Lectures
Time 02:10:44

You, This Course and Us

  • 02:01

Introduction

  • 10:26
  • 07:00
  • 06:01

Compute

  • 09:16
  • 07:38
  • 05:59
  • 08:12
  • 04:45
  • 04:43
  • 04:00
  • 10:33
  • 09:54
  • 06:55
  • 06:48
  • 06:03
  • 07:29

Storage

  • 09:48
  • 13:41
  • 10:37
  • 05:25
  • 03:52
  • 03:12
  • 07:09
  • 05:07
  • 05:32
  • 07:50
  • 09:28
  • 08:42

Cloud SQL, Cloud Spanner ~ OLTP ~ RDBMS

  • 07:40
  • 07:55
  • 06:31
  • 09:09
  • 07:25
  • 09:18
  • 06:49

BigTable ~ HBase = Columnar Store

  • 07:57
  • 08:12
  • 09:02
  • 08:10
  • 13:19
  • 07:39

Datastore ~ Document Database

  • 14:10
  • 06:42

BigQuery ~ Hive ~ OLAP

  • 11:03
  • 09:59
  • 09:04
  • 05:26
  • 07:28
  • 08:16
  • 07:45
  • 09:51
  • 05:44
  • 05:36
  • 10:45

Dataflow ~ Apache Beam

  • 11:04
  • 03:42
  • 12:56
  • 13:42
  • 11:17
  • 04:37
  • 09:50
  • 06:08
  • 15:50
  • 06:28

Dataproc ~ Managed Hadoop

  • 08:28
  • 08:11
  • 08:25
  • 07:39
  • 08:44
  • 02:10
  • 08:19

Pub/Sub for Streaming

  • 08:23
  • 05:35
  • 04:40
  • 05:52
  • 04:08
  • 08:18
  • 10:14
  • 05:54
  • 10:20

Datalab ~ Jupyter

  • 03:00
  • 04:01
  • 12:14
  • 06:43

TensorFlow and Machine Learning

  • 08:04
  • 10:27
  • 07:35
  • 07:16
  • 08:46
  • 10:17
  • 09:02
  • 05:03
  • 09:57
  • 08:44
  • 06:36
  • 07:49
  • 04:52
  • 08:05
  • 08:16
  • 08:06
  • 06:37
  • 04:13
  • 07:42
  • 07:31
  • 09:32
  • 14:14
  • 10:58
  • 09:52
  • 07:51
  • 10:27
  • 11:11

Regression in TensorFlow

  • 02:49
  • 05:53
  • 11:19
  • 09:56
  • 14:42
  • 09:15
  • 10:16
  • 05:25
  • 07:33
  • 08:33
  • 11:55
  • 12:13
  • 16:56
  • 04:10
  • 07:49
  • 04:54

Vision, Translate, NLP and Speech: Trained ML APIs

  • 14:38
  • 11:22
  • 10:54
  • 07:00

Virtual Machines and Images

  • 10:17
  • 09:21
  • 07:03
  • 02:22
  • 02:07
  • 07:45
  • 07:31

VPCs and Interconnecting Networks

  • 11:14
  • 11:19
  • 11:39
  • 05:46
  • 07:36
  • 15:33
  • 07:05
  • 19:32
  • 07:10
  • 07:27
  • 11:11
  • 10:31
  • 14:07
  • 08:10
  • 10:11
  • 06:17
  • 10:10
  • 07:17
  • 05:19

Managed Instance Groups and Load Balancing

  • 10:53
  • 05:46
  • 09:20
  • 08:31
  • 09:28
  • 04:28
  • 11:21
  • 07:06
  • 05:06
  • 07:49
  • 05:08
  • 07:16
  • 11:52
  • 12:22

Ops and Security

  • 12:08
  • 07:39
  • 08:12
  • 05:52
  • 06:05
  • 05:10
  • 08:27
  • 03:48
  • 08:53
  • 09:31
  • 11:57
  • 12:02

Appendix: Hadoop Ecosystem

  • 01:34
  • 09:43
  • 10:55
  • 10:34
  • 05:29
  • 07:19
  • 07:10
  • 07:36
  • 07:34
  • 08:22
  • 08:04
  • 06:38
  • 08:54
  • 11:45
  • 07:44
  • 05:40
  • 05:46
examvideo-11

About Professional Data Engineer: Professional Data Engineer on Google Cloud Platform Certification Video Training Course

Professional Data Engineer: Professional Data Engineer on Google Cloud Platform certification video training course by prepaway along with practice test questions and answers, study guide and exam dumps provides the ultimate training package to help you pass.

Professional Data Engineer on Google Cloud Platform is a track created by Google for certifying the professionals in the form of data engineers on Google Cloud Platform. The program helps the specialists on Google Cloud with the platform to reveal their skills by performing their best. The course not only includes the platform of Google Cloud but also considers some other platforms that includes Big Data, Managed Hadoop, and TensorFlow.

Description

With 60 demos and 25 contents, this course from Google Cloud Platform comes with a truly comprehensive guide. No doubt, it is quite lesser compared to other Google Platform certifications. To add to its adoption, the course also helps with advanced machines and learning apps, which assist in learning without any kind of hassles.

The Professional Data Engineer course prepares the candidate for the professional exam by explaining every important concept regarding data service of Google Cloud. The certification test also undertakes various tasks of the data engineer and helps in developing the skills accordingly which includes reliability, security, scalability, fault-tolerance, efficiency, and fidelity.

The course includes

  • Compute and Storage – AppEngine, Container Engineer, and Compute Engine
  • Managed Hadoop and Big Data– Dataproc, BigTable, Dataflow, Pub/Sub, BigQuery
  • TensorFlow on Cloud
  • DevOps stuff – StackDriver logging, observing, cloud arrangement chief
  • Security – Identity-Aware proxying, Identity and Access Management, API Keys, OAuth
  • Systems administration – Virtual Private Clouds, shared VPCs, Load adjusting at the system, transport and HTTP layer; VPN, Cloud Interconnect and CDN Interconnect
  • Hadoop Foundations

The course helps in the assessment of abilities like

  • Building and managing data structures and databases
  • Designing data processing system
  • Analyzing data and enabling machine learning
  • Model business process for optimization and analysis
  • Designing reliability
  • Visualizing data and policy of advocate
  • Designing for compliance and security

At the end of the course, the individuals would be capable of

  • Deploying the management of Hadoops apps on Google Cloud
  • Making informed decisions regarding VMs, AppEngine, and Containers
  • Building the models on Cloud with the help of TensonFlow
  • Use the big data technologies like Dataflow, Bigtable, Pub/Sub, and Apache Beam

The only requirement of the course is some basic knowledge regarding the technology, which is exposed off to Hadoop.

Exam details

  • The course comes with a total number of 90 questions.
  • The time given to complete the paper is 120 minutes.
  • The exam format includes multiple-choice questions.
  • The test can be given in languages like Japanese, Portuguese, English, and Spanish.

The preparations can be carried out with a number of study guides, e-books, PDF files, videos, quizzes, and much more.

Target audience

  • Anybody hoping to utilize the Google Cloud Platform in their associations
  • Anyone who is fascinating in architecting figure, organizing, adjusting the settings and different arrangements utilizing GCP
  • Anyone who needs to convey serverless investigation and huge information arrangements on Google Cloud
  • Anybody hoping to construct TensorFlow models and send them on Cloud

Conclusion

The Professional Data Engineer certification provided by Google Cloud Platform with a simple and negligible requirement hence is a good way to join Google and Cloud with easy to learn courses and interesting pay scale.

Career path:

  • Data Engineer
  • Data Scientist and Cognitive Engineer
  • Cloud Data Engineer
  • Software Engineer

The certification helps in getting a minimum pay of around $157,735 to $217,392 annually.

Prepaway's Professional Data Engineer: Professional Data Engineer on Google Cloud Platform video training course for passing certification exams is the only solution which you need.

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  • Premium File 163 Questions & Answers. Last update: Feb 19, 2021
  • Training Course 201 Lectures
  • Study Guide 543 Pages
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Free Professional Data Engineer Exam Questions & Google Professional Data Engineer Dumps
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Comments * The most recent comment are at the top

Anthony
United States
Feb 13, 2021
Astounding course with extraordinary inclinations. With the utilization of the course by the jewel of instructors for association level courses, I could clear the request course in the essential endeavor with fantastic numbers. The teacher has given his whole data in the course effectively with different uncovered gadgets to make it essential for reviewing. Along these lines, the training is ready to engage you to completely clear the certification exams.
Jaxon
Netherlands
Jan 24, 2021
I joined this course for a starting to GCP and was enjoyably shocked at the profundity and detail of the educational programs exhibited. Teachers were clear in their video introduction and straight to the point. Regions of enhancements would be: 1. A different segments material for Data Engineer and Cloud Architect. 2. More exam rehearses for every point. Generally speaking, highly prescribed course. Worth taking.
Hazel
Bulgaria
Jan 03, 2021
The course is efficient and most likely the main course, which covers the parts of the two Data designing and engineering. Despite the fact that this training is definitely not an extensive asset for clearing the exams, it sets up a decent construct for one to work in light of. I like the conveyance and enthusiasm of the educators in instructing. Lovely course to work with.
Luis
Rwanda
Dec 07, 2020
I earned my Google certification just by finishing this course. Its best part is Labs for every module. Bar Sub, Data Flow, and Big Query Integration Lab are such models where you become more acquainted with how unique bits of riddle fit together. I exceedingly suggest this course. Thanks for it!

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