Learning Apache Hadoop at Hadoop Express

Hadoop Express provides training on Big Data Hadoop, Java, Python, R and several other technologies. What distinguishes Hadoop Express is its ability to provide comprehensive learning features to students such as life time access to high quality course material, are account in Amazon cloud for hands-on practice, easy access to instructor, recorded videos of live classes, option to join their whatsapp student group and much more.
Hadoop Express is not just an online training without a physical presence. It has its learning center physically located at Parsippany, New Jersey at a beautiful office complex surrounded by many businesses. This brick-and-mortar location provides high quality education by highly experienced instructors and offers a chance for corporate executives to interact with students and staff of Hadoop Express.

For those who are new to Hadoop, free videos are provided on UNIX and Java to quickly catch up with pre-requisites for the course.

The Hadoop Professional Development course includes Map Reduce, Pig, Hive, Sqoop, Oozie and Hbase all of which are taught with explicit demos, examples and hands-on sessions. Options exist to also participate on projects.
Hadoop Express also provides software development assistance to other companies and trains business analysts and project managers on PMP certification so that they may pass the certification on their first attempt and secure project management jobs.
The course provides quick introduction to essential features of Hadoop and its family of products (called ecosystem) so that a starter on Hadoop may quickly start coding in a Hadoop environment. Unlike most other courses which require students to install a VM from a Hadoop provider like Cloudera and Hortonworks, Hadoop Express provides access to students to an Amazon instance of Hadoop cluster. This saves resources on student local laptops as most of these VMs are very memory intensive and require several gigs of RAM.
Further, Hadoop Express is also building its own Big Data products which are expected to be launched this year (2017). Students are encouraged to take part in its product manufacturing initiatives to get hands-on experience eon a live project.