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=Basic Info=
GCDEC: Google Cloud Data Engineer Certification


Links:
==Basic Info==
* Certification info: https://cloud.google.com/certification/data-engineer
* Sample case study: https://cloud.google.com/certification/guides/data-engineer/casestudy-flowlogistic
* Tutorials/Guides/Resources for all of Google Cloud: https://cloud.google.com/solutions/


Stack:
Certification overview: https://cloud.google.com/certification/data-engineer
* See [[Google Cloud]]
 
Sample case study: https://cloud.google.com/certification/guides/data-engineer/casestudy-flowlogistic
 
What this certification "certifies" you can do:
* Build and maintain data structures and databases
* Design data processing systems
* Analyze data and enable machine learning
* Model business processes for analysis and optimization
* Design for reliability
* Visualize data and advocate policy
* Design for security and compliance
 
Underlying goal: building data-handling capabilities (pipelines to ingest, process, and analyze data, and build models)
* Data engineers enable better decision-making
* Cloud services enable you to do more stuff with less knowledge and work - more infrastructure and better models, without getting bogged down by rote devops tasks or slogging through low-level statistics
 
==What is a Data Engineer==
 
Data engineers do any number of things:
* Design, build, and maintain data structures, databases, data processing systems, data pipelines
* Move data from one place to another
* Data science
* Enabling machine learning to happen, doing machine learning themselves
* Model the process
* Enable data-driven decision making in a company
 
==Google Cloud Services==
 
See [[Google Cloud#Google Cloud Services]]
 
==Technology Stack==
 
Case study with an example of the kind of technology stack that you might see in use at a company:
* [[Google Cloud/Case Study]]
 
List of all pages related to Google Cloud platform:
* [[:Category:Google Cloud]]
 
==Training Resources==
 
===Coursera===
 
Course 1 - Google Cloud Platform Big Data and Machine Learning Fundamentals
* [[GCDEC/Fundamentals/Notes]]
 
Course 2 - Leveraging Unstructured Data with Cloud Dataproc
* [[GCDEC/Unstructured Data/Notes]]
 
Course 3a - Serverless Data Analysis with BigQuery
* [[GCDEC/BigQuery/Notes]]
 
Course 3b - Serverless Data Analysis with Dataflow
* [[GCDEC/Dataflow/Notes]]
 
Course 4a - Building Machine Learning Models with Tensorflow (not necessarily in the cloud...)
* [[GCDEC/Building Tensorflow/Notes]]
 
Course 4b - Deploying Machine Learning Models with Tensorflow (in the cloud)
* [[GCDEC/Deploying Tensorflow/Notes]]
 
Course 4c - Engineering Machine Learning Models with Tensorflow (feature engineering and pipelining in the cloud)
* [[GCDEC/Engineering Tensorflow/Notes]]
 
Course 5 - Building Resilient Streaming Systems
* [[GCDEC/Streaming/Notes]]
 
===Udemy===
 
GCDE practice exams
 
[[GCDE/Practice Exam 1]] - Taken 9/29/17. Mostly missed questions covering Dataproc.
 
===Labs===
 
<s>Code Labs, GCP Essentials Quest: https://google.qwiklabs.com/quests/23?locale=en</s>
 
Code Labs, Data Engineering Quest: https://google.qwiklabs.com/quests/25?locale=en
 
Code Labs, Scientific Data Quest: https://google.qwiklabs.com/quests/28?locale=en
 
===Certification Outline===
 
Sample case study link: https://cloud.google.com/certification/guides/data-engineer/casestudy-flowlogistic
 
Outline of topics covered by exam link: https://cloud.google.com/certification/guides/data-engineer/#certificate-exam-guide
 
Analysis of outline of topics: [[GCDE/Outline of Topics]]
 
=Flags=
 
[[Category:Google Cloud]]
[[Category:Data Engineering]]

Latest revision as of 02:11, 19 December 2017

GCDEC: Google Cloud Data Engineer Certification

Basic Info

Certification overview: https://cloud.google.com/certification/data-engineer

Sample case study: https://cloud.google.com/certification/guides/data-engineer/casestudy-flowlogistic

What this certification "certifies" you can do:

  • Build and maintain data structures and databases
  • Design data processing systems
  • Analyze data and enable machine learning
  • Model business processes for analysis and optimization
  • Design for reliability
  • Visualize data and advocate policy
  • Design for security and compliance

Underlying goal: building data-handling capabilities (pipelines to ingest, process, and analyze data, and build models)

  • Data engineers enable better decision-making
  • Cloud services enable you to do more stuff with less knowledge and work - more infrastructure and better models, without getting bogged down by rote devops tasks or slogging through low-level statistics

What is a Data Engineer

Data engineers do any number of things:

  • Design, build, and maintain data structures, databases, data processing systems, data pipelines
  • Move data from one place to another
  • Data science
  • Enabling machine learning to happen, doing machine learning themselves
  • Model the process
  • Enable data-driven decision making in a company

Google Cloud Services

See Google Cloud#Google Cloud Services

Technology Stack

Case study with an example of the kind of technology stack that you might see in use at a company:

List of all pages related to Google Cloud platform:

Training Resources

Coursera

Course 1 - Google Cloud Platform Big Data and Machine Learning Fundamentals

Course 2 - Leveraging Unstructured Data with Cloud Dataproc

Course 3a - Serverless Data Analysis with BigQuery

Course 3b - Serverless Data Analysis with Dataflow

Course 4a - Building Machine Learning Models with Tensorflow (not necessarily in the cloud...)

Course 4b - Deploying Machine Learning Models with Tensorflow (in the cloud)

Course 4c - Engineering Machine Learning Models with Tensorflow (feature engineering and pipelining in the cloud)

Course 5 - Building Resilient Streaming Systems

Udemy

GCDE practice exams

GCDE/Practice Exam 1 - Taken 9/29/17. Mostly missed questions covering Dataproc.

Labs

Code Labs, GCP Essentials Quest: https://google.qwiklabs.com/quests/23?locale=en

Code Labs, Data Engineering Quest: https://google.qwiklabs.com/quests/25?locale=en

Code Labs, Scientific Data Quest: https://google.qwiklabs.com/quests/28?locale=en

Certification Outline

Sample case study link: https://cloud.google.com/certification/guides/data-engineer/casestudy-flowlogistic

Outline of topics covered by exam link: https://cloud.google.com/certification/guides/data-engineer/#certificate-exam-guide

Analysis of outline of topics: GCDE/Outline of Topics

Flags

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