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学生对 Google 云端平台 提供的 Building Resilient Streaming Systems on Google Cloud Platform 的评价和反馈

4.7
1,657 个评分
122 个审阅

课程概述

This 1-week, accelerated on-demand course builds upon Google Cloud Platform Big Data and Machine Learning Fundamentals. Through a combination of video lectures, demonstrations, and hands-on labs, you'll learn how to build streaming data pipelines using Google Cloud Pub/Sub and Dataflow to enable real-time decision making. You will also learn how to build dashboards to render tailored output for various stakeholder audience. Prerequisites: • Google Cloud Platform Big Data and Machine Learning Fundamentals (or equivalent experience) • Some knowledge of Java Objectives: • Understand use-cases for real-time streaming analytics • Use Google Cloud PubSub asynchronous messaging service to manage data events • Write streaming pipelines and run transformations where necessary • Get familiar with both sides of a streaming pipeline: production and consumption • Interoperate Dataflow, BigQuery and Cloud Pub/Sub for real-time streaming and analysis...

热门审阅

PG

Aug 25, 2018

This course was very helpful to understand how to built high throughput streaming work flows on google cloud. It described in detail how to model big table for efficient application.

CC

Aug 19, 2017

Course gives nice overview of Bigtable, when to use it compared to bigquery. flowchart describing the when to use which product is really helpful. Thanks Lak for the course.

筛选依据:

1 - Building Resilient Streaming Systems on Google Cloud Platform 的 25 个评论(共 121 个)

创建者 Sudeshna D

Dec 20, 2018

good

创建者 Peter S

Dec 20, 2018

Very interesting!!

创建者 William M

Jan 31, 2019

I recommend this course to learn the fundamentals of Building Resilient Streaming Systems on Google Cloud Platform

创建者 Flavio d R

Nov 20, 2018

Good overview of streaming architecture, coupled with realistic use cases in the labs.

创建者 Mikhail M

Nov 21, 2018

Very Nice!

创建者 Onur U

Nov 26, 2018

Streaming pull on Pub/Sub can also be added.

How to get publish time and message id those are added on Pub/Sub on Dataflow can also be mentioned.

创建者 Javier R

Jan 16, 2019

Very useful.

创建者 Preetish K D

Jan 09, 2019

All concept explained nicely.

创建者 Adam E

Feb 06, 2019

Sick

创建者 Mnason A P

Feb 16, 2019

great

创建者 Christof G v R

Feb 16, 2019

Though the subject was the most obscure and least relevant to me of all 5 courses in the specialization, I think I learned the most during this one.

创建者 Chandrasekar B

Feb 27, 2019

good

创建者 Alejandro J A

Feb 27, 2019

Un curso maravilloso.

创建者 Brian C G

Mar 04, 2019

Excellent course! Great exercises and a solid background on how to build resilient streaming systems with GCP

创建者 Julian K

Mar 06, 2019

This was a pleasure to attend. Some minor frustrations when tests failed or just stopped, but support was excellent and by revisiting your site 2 stopped tests resulted in a pass! Note that some of the current web pages have changed since the course was created - so the tests are more real-world as you have to figure stuff out yourself - not such a bad thing!

创建者 Vicente G d S

Mar 19, 2019

Excelent way of learning Pub Sub.

创建者 Amit K

Dec 28, 2018

Good

创建者 Raja R G

Dec 29, 2018

Very Good content...

创建者 Michael S P P

Aug 08, 2018

Estos cursos permiten incursionar en la plataforma Google Cloud, es básico y hace falta pasar más tiempo con la plataforma y crear un proyecto grande, pero para empezar está bastante bien.

创建者 Parag G

Aug 25, 2018

This course was very helpful to understand how to built high throughput streaming work flows on google cloud. It described in detail how to model big table for efficient application.

创建者 Jaskarandeep P

Oct 16, 2018

great Learning Experience

创建者 Girish O

Oct 19, 2018

Thank you Lak for a wonderful journey through GCP, ML and Big Data

创建者 Soumya R B

Sep 15, 2018

Awesome

创建者 Rambabu A

Sep 15, 2018

Wonderful and powerful features in google ... Ultimate Powerful cloud Platform

创建者 harada h

Sep 26, 2018

This has been a great course. All the theory and practical content I find useful to get me started in the field of machine learning