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Udemy - Apache Spark with Python – Big Data with PySpark and Spark

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Description

What is this course about:

This course
covers all the fundamentals about Apache Spark with Python and teaches you everything you need to know about developing
Spark applications using PySpark, the Python API for Spark. At the end of this course, you will gain in-depth knowledge
about Apache Spark and general big data analysis and manipulations skills to help your company to adapt Apache Spark for
building big data processing pipeline and data analytics applications.

This course covers 10+ hands-on big
data examples. You will learn valuable knowledge about how to frame data analysis problems as Spark problems. Together
we will learn examples such as aggregating NASA Apache web logs from different sources; we will explore the price trend
by looking at the real estate data in California; we will write Spark applications to find out the median salary of
developers in different countries through the Stack Overflow survey data; we will develop a system to analyze how maker
spaces are distributed across different regions in the United Kingdom. And much much more.

What will you
learn from this lecture:

In particularly, you will learn:

 An overview of the architecture of
Apache Spark.
 Develop Apache Spark 2.0 applications with PySpark using RDD transformations and actions and Spark
SQL.
 Work with Apache Spark’s primary abstraction, resilient distributed datasets(RDDs) to process and
analyze large data sets.
 Deep dive into advanced techniques to optimize and tune Apache Spark jobs by
partitioning, caching and persisting RDDs.
 Scale up Spark applications on a Hadoop YARN cluster through
Amazon’s Elastic MapReduce service.
 Analyze structured and semi-structured data using Datasets and
DataFrames, and develop a thorough understanding of Spark SQL.
 Share information across different nodes on an
Apache Spark cluster by broadcast variables and accumulators.
 Best practices of working with Apache Spark in the
field.
 Big data ecosystem overview.

Why should you learn Apache Spark:

Apache Spark
gives us unlimited ability to build cutting-edge applications. It is also one of the most compelling technologies of the
last decade in terms of its disruption to the big data world.

Spark provides in-memory cluster computing
which greatly boosts the speed of iterative algorithms and interactive data mining tasks.

Apache Spark is the
next-generation processing engine for big data.

Tons of companies are adapting Apache Spark to extract
meaning from massive data sets, today you have access to that same big data technology right on your desktop.

Apache Spark is becoming a must tool for big data engineers and data scientists.

What programming
language is this course taught in?

This course is taught in Python. Python is currently one of the most
popular programming languages in the world! It’s rich data community, offering vast amounts of toolkits and
features makes it a powerful tool for data processing. Using PySpark (the Python API for Spark) you will be able to
interact with Apache Spark’s main abstraction, RDDs, as well as other Spark components, such as Spark SQL and
much more!

Let’s learn how to write Spark programs with PySpark to model big data problems today!

30-day Money-back Guarantee!

You will get 30-day money-back guarantee from Udemy for this course.

If not satisfied simply ask for a refund within 30 days. You will get a full refund. No questions whatsoever
asked.

Are you ready to take your big data analysis skills and career to the next level, take this course
now!

You will go from zero to Spark hero in 4 hours.
Who is the target audience?


Anyone who want to fully understand how Apache Spark technology works and learn how Apache Spark is being used in the
field.
 Software engineers who want to develop Apache Spark 2.0 applications using Spark Core and Spark SQL.

Data scientists or data engineers who want to advance their career by improving their big data processing skills. 
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