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学生对 加州大学戴维斯分校 提供的 Distributed Computing with Spark SQL 的评价和反馈

4.4
127 个评分
35 条评论

课程概述

This course is for students with SQL experience and now want to take the next step in gaining familiarity with distributed computing using Spark. Students will gain an understanding of when to use Spark and how Spark as an engine uniquely combines Data and AI technologies at scale. The four modules build on one another and by the end of the course the student will understand: Spark architecture, Spark DataFrame, optimizing reading/writing data, and how to build a machine learning model. The first module will introduce Spark, including how Spark works with distributed computing and what are Spark Dataframes. Module 2 covers the core concepts of Spark such as storage vs. computing, caching, partitions and Spark UI. The third module looks at Engineering Data Pipelines covering connecting to databases, schemas and type, file formats and writing good data. The final module looks at the application of Spark with Machine Learning through the business use case, a short introduction to what machine learning is, building and applying models and a final course conclusion. By understanding when to use Spark, either scaling out when the model or data is too large to process on a single machine, or having a need to simply speed up to get faster results, students will hone their SQL skills and become a more adept Data Scientist....

热门审阅

GT

Jun 10, 2020

I highly recommend this course for anyone in the BI and Data space interested in learning Spark. The course gives an easy to understand to the framework and applicable hands on examples.

KS

May 14, 2020

Amazing course that really cuts through the fundamentals of using distributed computing power to analyze and manipulate data. Well organised structure on fundamentals

筛选依据:

1 - Distributed Computing with Spark SQL 的 25 个评论(共 36 个)

创建者 Steven O

Apr 06, 2020

A more appropriate title for the class would be "a brief introduction to Databricks". Very disappointing class. There are Youtube tutorials out there with more content than this class. This is one of the only classes that I have ever taken on Coursera where I could complete 2 weeks worth of all the lectures, assignments, and quizzes in a Sunday afternoon. I think this class was hastily slapped together, there is so little content. If your organization uses Spark and is not a Databricks client (as mine is), you will learn absolutely nothing here. The lectures are extremely short and devoid of any substance. I am still looking for a good online class in Spark. It certainly is not this one.

创建者 Sacha v W

Feb 19, 2020

very superficial using databricks. The courses misses depth to be of any use. It is more a Databricks commercial. Executing pieces of available course without sufficient practice

创建者 Joseph B

Jan 06, 2020

Extremely informative for those who are seeking to learn the fundamentals for distributed computing using Spark SQL.

创建者 md z a

Mar 04, 2020

Expecting more advance material

创建者 Deepika S

May 20, 2020

This course is a great learning source for Distributed Computing with Spark SQL. I got started with course and learnt basic concepts, dos and don'ts.

Concepts are explained well and work notebooks provided needed hands on experience.

Thanks for the course.

Best,

Deepika Sharma

创建者 Serjesh S

May 29, 2020

I wanted to quickly revisit spark sql on Databricks platform after last time using spark (on premise)3 years ago .This course provided perfect refresher to all the important concepts.Module 4 is specifically pleasant and take it little closer to BigQueryML.

创建者 George T

Jun 10, 2020

I highly recommend this course for anyone in the BI and Data space interested in learning Spark. The course gives an easy to understand to the framework and applicable hands on examples.

创建者 Kumar S

May 14, 2020

Amazing course that really cuts through the fundamentals of using distributed computing power to analyze and manipulate data. Well organised structure on fundamentals

创建者 Elliot T

Jul 13, 2020

Great introduction to Spark with Databricks that seems to be an intuituve tool! Really cool to do the link between SQL and Data Science with a basic ML example!

创建者 Dilin J K J

Feb 12, 2020

This has been an amazing course. What is worth mentioning is how the content was delivered. Nice hands on. Highly recommended for anyone who is new to Spark

创建者 Oisin D

Mar 26, 2020

Great course, really well taught and delivered. Only thing I would say is you would really need knowledge of python to really understand this course 100%

创建者 Isaac T

Feb 23, 2020

Great introduction to Spark SQL and ML Flow. I love that they give extra resources if you want to learn more. It was a fun learning journey.

创建者 Tina M

Apr 26, 2020

The information was very beneficial, and the ability to use data bricks

helped put into practice the information learned.

创建者 GANESH H

Jul 02, 2020

Good course for understanding the distributed computing and how the machine learning is down in spark environment.

创建者 Tejas S M

Apr 19, 2020

It is a nice experience to learn and a great course to understand the spark's core architecture.

创建者 Fenil P

May 07, 2020

kudos to the instructor who teach this course by clearing all the concepts of spark sql:)

创建者 Sebastien C

Jul 10, 2020

Very well structured and easy to follow. The assignements are where we lear the most!

创建者 Rob E

Jul 06, 2020

Great course. The pedagogy and content were very well done.

创建者 Mohammad M R

Apr 17, 2020

Good course for spark

创建者 David M G

May 02, 2020

Fantastic Course!

创建者 Pablo S L

Mar 27, 2020

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创建者 Borusyk O

May 25, 2020

Nice work! Thnx

创建者 Katerine C

Jul 05, 2020

Very good

创建者 ANDRES F C

May 25, 2020

great

创建者 Kota M

Apr 29, 2020

Very great introduction to the Spark SQL and databricks environment worked perfectly as a hands-on.

It would be great if the course covers the Spark ML applications. We used sklearn in the course and utilized a trained model by using the user-defined function. I wonder how it compares with the case where we use Sp ark ML for the training as well.