The Big Data Hadoop developer course have been designed to provide an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab
The course provides you with an in-depth understanding of the Hadoop framework including HDFS, YARN, and MapReduce. You will learn to use Pig, Hive, and Impala to process and analyze large datasets stored in the HDFS, and use Sqoop and Flume for data ingestion.
As a part of the course, you will be required to execute real-life industry-based projects using CloudLab. The projects included are in the domains of Banking, Telecommunication, Social media, Insurance, and E-Commerce. This Big Data course also prepares you for the Cloudera CCA175 certification.
Curriculum designed along with large National Industry Partners + Guest speakers from Harvard University to Industry Partners.
Trainees will work on live projects as a part of the training program. 90% of each course involves "Learning by Doing" using state-of-the-art computers for performing hands-on exercises and real-world simulations..
We are passionate about the power of good leadership and management to transform people and organisations. We believe that, with the right training and development, everyone can be a better leader and manager..
Strong Soft Skills, Client Handling skills, Personality development skills, working in teams, presentation & communication skills.
We believe in one to one training and so we follow this practice, we understand it is very hard to manage a class of n-number of students for us and deliverables are always messy for both, delivering and receiving end.
We will provide assured paid work experience certificates to our each and every trainee after successfully completion of the training.
An online, open source website creation tool written in PHP. But in non-geek speak, it’s probably the easiest and most powerful blogging and website CMS in existence today.
If you felt like you just read a lot it, it’s because we do a lot, Let's meet over a cup of coffee to discuss in detail.