PySpark Certification Training Course

Learning Objectives: In this module, you will learn about SparkSQL which is used to process structured data with SQL queries. You will learn about data-frames and datasets in Spark SQL along with different kind of SQL operations performed on the data-frames. You will also learn about the Spark and Hive integration. 

Learning Objectives: In this module, you will understand Kafka and Kafka Architecture. Afterward, you will go through the details of Kafka Cluster and you will also learn how to configure different types of Kafka Cluster. After that you will see how messages are produced and consumed using Kafka API’s in Java. You will also get an introduction to Apache Flume, its basic architecture and how it is integrated with Apache Kafka for event processing. You will learn how to ingest streaming data using flume. 

There are no prerequisites for the PySpark training course. Prior work experience is also not required. Knowledge of Python programming and SQL will be an added advantage.

You will learn about HDFS, Hadoop 2.x, the Spark ecosystem, Spark SQL, and MLlib. The course also covers real-time data processing with Kafka, Flume, and Spark Streaming. Additionally, you will work on practical projects using Edureka’s CloudLab.

You are required to complete all your assignments and Case Studies using the VM provided by Edureka. In case you have any doubts or questions, Edureka’s Support Team will be available 24/7 for prompt assistance.

It would help if you had good internet connectivity and a Mobile/tab/laptop/system installed with Zoom/Meet, which is required for the PySpark online training. In addition, we will provide Cloud LAB, a pre-configured environment with the necessary tools and services for executing your practicals.

Once payment is received, you will automatically receive a payment receipt and access information via email.

You don’t have to worry about the system requirements as you will be executing your practicals on a Cloud LAB which is a pre-configured environment. This environment already contains all the necessary tools and services required for Edureka's PySpark Training.

At the end of the PySpark Training, you will be assigned with real-life use-cases as certification projects to further hone your skills and prepare you for the various Spark Developer Roles. Following are few industry-specific case studies that are included in our Apache Spark Developer Certification Training.

Project 1- Domain: Financial

Statement: A leading financial bank is trying to broaden the financial inclusion for the unbanked population by providing a positive and safe borrowing experience. In order to make sure this underserved population has a positive loan experience, it makes use of a variety of alternative data--including telco and transactional information--to predict their clients' repayment abilities. The bank has asked you to develop a solution to ensure that clients capable of repayment are not rejected and that loans are given with a principal, maturity, and repayment calendar that will empower their clients to be successful.

Project 2- Domain: Transportation Industry

Business challenge/requirement: With the spike in pollution levels and the fuel prices, many Bicycle Sharing Programs are running around the world. Bicycle sharing systems are a means of renting bicycles where the process of obtaining membership, rental and bike return is automated via a network of joint locations throughout the city. Using this system people can rent a bike from one location and return it to a different place as and when needed.

Considerations: You are building a Bicycle Sharing demand forecasting service that combines historical usage patterns with weather data to forecast the Bicycle rental demand in real-time. To develop this system, you must first explore the dataset and build a model. Once it’s done you must persist the model and then on each request run a Spark job to load the model and make predictions on each Spark Streaming request