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Packt - Scala and Spark-Master Big Data with Scala and Spark

Hannibal Ebooks & Tutorials 23 Sep 2021, 22:03 0
Packt - Scala and Spark-Master Big Data with Scala and Spark

Packt - Scala and Spark-Master Big Data with Scala and Spark-XQZT
English | Size: 7.35 GB
Category: Tutorial

Learn Scala; learn Spark, Hadoop, ETL pipeline from AWS S3 to AWS RDS using Spark from scratch
Packt - Scala and Spark-Master Big Data with Scala and Spark

Packt - Scala and Spark-Master Big Data with Scala and Spark-XQZT
English | Size: 7.35 GB
Category: Tutorial

Learn Scala; learn Spark, Hadoop, ETL pipeline from AWS S3 to AWS RDS using Spark from scratch
The course Scala from Beginner to Pro is refreshingly different. The well-thought-out quizzes and mini projects that cover all the important aspects will make your Scala learning journey that much easier. This course includes an overview of Hadoop and Spark with a hands-on project with Scala Spark. Right through the course, every theoretical explanation is followed by practical implementation.

This course is designed to reflect the most in-demand Scala skills that you will start using right away at the workplace. The course is simple to follow and understand. Expressive, exhaustive, and practical with live coding sessions and replete with quizzes. Rich with state-of-the-art and up-to-date knowledge of this field.

The 6 mini-projects and one Scala Spark project included in this course are a vital component of this course. These projects present you with a hands-on opportunity to experiment for yourself with trial and error. You get a chance to learn from the mistakes you make. Importantly, it's easy to understand the potential gaps that might exist between theory and practice.

Another exquisit release

Packt.Scala.and.Spark-Master.Big.Data.with.Scala.and.Spark-XQZT

Title: Scala & Spark-Master Big Data with Scala and Spark
Publisher: Packt
Category: Data
Size: 7541M
Files: 13F
Date: 2021-08-29
Course #: 9781803248653
Published: Packt
Updated: N/A
Author: AI Sciences
Duration: 12 hours 47 minutes
Exer/Code:

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