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Distributed Computing with Spark SQL

This course is a part of Learn SQL Basics for Data Science, a 4-course Specialization series from Coursera.

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.

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University of California, Davis

Rating 3.7 based on 4 ratings
Length 5 weeks
Effort 4 weeks of study, 2-5 hours/week
Starts Feb 17 (last week)
Cost $49
From University of California, Davis via Coursera
Instructors Brooke Wenig, Conor Murphy
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science Programming
Tags Data Science Data Analysis Machine Learning

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executing pieces of available in one review

Executing pieces of available course without sufficient practice This has been an amazing course.

available course without sufficient in one review

very superficial using databricks in one review

very superficial using databricks.

highly recommended for anyone in one review

Highly recommended for anyone who is new to Spark Extremely informative for those who are seeking to learn the fundamentals for distributed computing using Spark SQL.

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content was delivered in one review

What is worth mentioning is how the content was delivered.

courses misses depth in one review

The courses misses depth to be of any use.

video quality needs in one review

video quality needs to be improved.

databricks commercial in one review

It is more a Databricks commercial.

nice hands in one review

Nice hands on.

any use in one review

careful about in one review

Be careful about the last assignment.

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Coursera

&

University of California, Davis

Rating 3.7 based on 4 ratings
Length 5 weeks
Effort 4 weeks of study, 2-5 hours/week
Starts Feb 17 (last week)
Cost $49
From University of California, Davis via Coursera
Instructors Brooke Wenig, Conor Murphy
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science Programming
Tags Data Science Data Analysis Machine Learning

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