Distributed Computing with Spark SQL
Learn SQL Basics for Data Science,
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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| Rating | 3.7★ based on 4 ratings |
|---|---|
| Length | 5 weeks |
| Effort | 4 weeks of study, 2-5 hours/week |
| Starts | Dec 7 (7 weeks ago) |
| 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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What people are saying
executing pieces of available
Executing pieces of available course without sufficient practice This has been an amazing course.
available course without sufficient
very superficial using databricks
very superficial using databricks.
highly recommended for anyone
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.
fundamentals for distributed computing
content was delivered
What is worth mentioning is how the content was delivered.
courses misses depth
The courses misses depth to be of any use.
video quality needs
video quality needs to be improved.
databricks commercial
It is more a Databricks commercial.
nice hands
Nice hands on.
any use
careful about
Be careful about the last assignment.
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| Rating | 3.7★ based on 4 ratings |
|---|---|
| Length | 5 weeks |
| Effort | 4 weeks of study, 2-5 hours/week |
| Starts | Dec 7 (7 weeks ago) |
| 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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