Python and Spark for Big Data (PySpark) Training Course

Python е език за програмиране на високо ниво, известен със своя ясен синтаксис и четливост на кода. Spark е машина за обработка на данни, използвана при заявки, анализиране и трансформиране на големи данни. PySpark позволява на потребителите да взаимодействат между Spark и Python.

В това водено от инструктор обучение на живо участниците ще се научат как да използват Python и Spark заедно, за да анализират големи данни, докато работят върху практически упражнения.

До края на това обучение участниците ще могат:

Научете как да използвате Spark с Python за анализ на големи данни. Работете върху упражнения, които имитират случаи от реалния свят. Използвайте различни инструменти и техники за анализ на големи данни с помощта на PySpark.

Формат на курса

Част лекция, част дискусия, упражнения и тежка практическа практика

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Oтзиви от потребители (5)

I liked that it was practical. Loved to apply the theoretical knowledge with practical examples.

Aurelia-Adriana - Allianz Services Romania

Course - Python and Spark for Big Data (PySpark)

The course was about a series of very complex related topics & Pablo has in-depth expertise of each of them. Sometimes nuances were lost in communication and/or due to time pressures and possibly expectations were not quite met due to this. Also there were some UHG/Azure Databricks setup issues however Pablo / UHG resolved these quickly once they became apparent - this to me showed a high level of understanding and professionalism between UHG & Pablo,

Michael Monks - Tech NorthWest Skillnet

Course - Python and Spark for Big Data (PySpark)

Individual attention.

ARCHANA ANILKUMAR - PPL

Course - Python and Spark for Big Data (PySpark)

Hands on Training..

Abraham Thomas - PPL

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.