Star Innovations

Programming in Big Data Hadoop

About this Course
In this hadoop training course, participants will learn to:

Work with the problems of Big Data in real life situation.
Develop MapReduce applications using Java.
Handle No-SQL databases.
Work with the process of Data Transfer and Data Handling using Apache Sqoop and Flume.
Handling Workflow Management using Oozie.
Big Data Platforms – Hortonworks and GreenPlum.
Cloudera’s Hadoop Distribution and Management Tools.
The participants learn big data programming and will be ready to work with Big Data problems using Apache Hadoop and its frameworks, along with other tools and frameworks of Hadoop and its eco-system.

The hadoop training will comprise of a series of lectures aided by demonstrations and followed by hands-on session on the prescribed equipment and/or software that the course is designed to cover.

Some amount of preparation by the participant is expected, for each session, using the course material available in the form of printed books.

Post each session on learning big data programming, the participant is expected to revise the concepts and work on exercises provided.

There is a project that will be assigned mid-way through the hadoop training. The project will carry a significant portion of the marks that will decide the grade obtained by a student on completing the course.

The other form of assessment will be an online exam comprising of Multiple Choice Questions at the end of the module.

Course Syllabus
All learners who register on or after May 1, 2017 will get access to the digitized courseware online on Digital Hub and no hard copy of courseware will be issued.

There are 8 modules

01 MODULE
No SQL Databases
Brief Description:
This module covers the concepts of NoSQL databases and their implementation.
Recommended Learning Duration:
20 Hours

02 MODULE
Introduction to Big Data and Working with Hadoop
Brief Description:
This module covers the concepts of Big Data Hadoop and its problems.
Recommended Learning Duration :
30 Hours

03 MODULE
Application Development using MapReduce and Java
Brief Description:
This module covers the programming concept of mapreduce using Java.
Recommended Learning Duration:
20 Hours

04 MODULE
Data Transfer and Data Handling using Apache Sqoop and Flume
Brief Description:
This module covers the concepts of Data transfer using Sqoop and handling streaming data by using Flume.
Recommended Learning Duration:
20 Hours

05 MODULE
Workflow Management using Oozie
Brief Description:
This module covers the concepts of handling workflows using OOzie.
Recommended Learning Duration:
10 Hours

06 MODULE
Big Data Platforms – Hortonworks and GreenPlum
Brief Description:
This module deals with the Big data frameworks.
Recommended Learning Duration:
10 Hours

07 MODULE
Cloudera’s Hadoop Distribution and Management Tools
Brief Description:
This module deals with Cloudera framework of Hadoop.
Recommended Learning Duration:
10 Hours

08 MODULE
Soft Skills
Brief Description:
This module is to groom the candidates and make them market ready.
Recommended Learning Duration:
20 Hours
Final Exam- Online, Proctored
This is the final evaluation module of learning.

More Info