PySpark for Data Science – Beginners
Learn basics of Apache Spark and learn to analyze Big Data for Machine Learning using Python in PySpark.
What you’ll learn
- Learn bout the concept of RDDs and other very basic features and terminologies being used in the case of Spark
- You will also understand what are the benefits and disadvantages of using Spark
- Use Python with Big Data on Apache Spark
- These PySpark Tutorials aims to explain the basics of Apache Spark and the essentials related to it
- The pre-requisite of these PySpark Tutorials is not much except for that the person should be well familiar and should have a great hands-on experience in any of the languages such as Java, Python or Scala or their equivalent. The other pre-requisites include the development background and the sound and fundamental knowledge of big data concepts and ecosystem as Spark API is based on top of big data Hadoop only.
These PySpark Tutorials aim to explain the basics of Apache Spark and the essentials related to it. This also targets why the Apache spark is a better choice than Hadoop and is the best solution when it comes to real-time processing. You will also understand what are the benefits and disadvantages of using Spark with all the above-listed languages You will also read about the concept of RDDs and other very basic features and terminologies being used in the case of Spark. This course is for students, professionals, and aspiring data scientists who want to get hands-on training in PySpark (Python for Apache Spark) using real-world datasets and applicable coding knowledge that you’ll use every day as a data scientist.
Pyspark is a big data solution that is applicable for real-time streaming using Python programming language and provides a better and efficient way to do all kinds of calculations and computations. It is also probably the best solution in the market as it is interoperable i.e. The earlier big data and Hadoop techniques included batch time processing techniques.
Who this course is for:
- The target audience for these PySpark Tutorials includes ones such as the developers, analysts, software programmers, consultants, data engineers