Online or onsite, instructor-led live PySpark training courses demonstrate through hands-on practice how to use Python and Spark together to analyze big data.
PySpark training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Indonesia onsite live PySpark trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
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Testimonials
practice tasks
Pawel Kozikowski - GE Medical Systems Polska Sp. Zoo
Course: Python and Spark for Big Data (PySpark)
* Organization * Trainer's expertise with the subject
ENGIE- 101 Arch Street
Course: Python and Spark for Big Data (PySpark)
The lessons were taught in a Jupyter notebook. The topics were structured with a logical sequence and naturally helped develop the session from the easier parts to the more complex. I'm already an advanced user of Python with background in Machine Learning, so found the course easier to follow than, possibly, some of my classmates that took the training course. I appreciate that some of the most elementary concepts were skipped and that he focused on the most substantial matters.
Angela DeLaMora - ADT, LLC
Course: Python and Spark for Big Data (PySpark)
NA
DBS
Course: Python and Spark for Big Data (PySpark)
hands on Training..
Abraham Thomas - PPL
Course: Python and Spark for Big Data (PySpark)
individual attention.
ARCHANA ANILKUMAR - PPL
Course: Python and Spark for Big Data (PySpark)
The teacher has adapted the training program to our current needs.
EduBroker Sp. z o.o.
Course: Python and Spark for Big Data (PySpark)
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PySpark Course Outlines in Indonesia
Course Name
Duration
Overview
Course Name
Duration
Overview
21 hours
In this instructor-led, live training in Indonesia, participants will learn how to use Python and Spark together to analyze big data as they work on hands-on exercises.
By the end of this training, participants will be able to:
- Learn how to use Spark with Python to analyze Big Data.
- Work on exercises that mimic real world cases.
- Use different tools and techniques for big data analysis using PySpark.
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