Certificate Programme on System Integration : Big Data
Details
In this course, the participants will learn to:
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Work with the problems of Big Data in real life situation.
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Develop advanced Algorithms and OO concepts using Java.
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Develop MapReduce applications using Java.
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Work with Python Scripting.
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Handle No-SQL databases.
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Work with the process of Data Transfer and Data Handling using Apache Sqoop and Flume.
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Handling Workflow Management using Oozie.
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Big Data Platforms - Hortonworks and GreenPlum.
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Cloudera's Hadoop Distribution and Management Tools.
Outcomes: The participants 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 course 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, 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 course. 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.
By purchasing or subscribing to this program, you agree to abide by the Usage Policy, Privacy Policy, Security Policies and any Terms and Conditions mentioned on this portal.
Please note, this course offered by TCS iON is for learning facilitation only with no placement assistance associated with it.
This Course Is Best For
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High School/Undergraduates with knowledge of programming language and database and who want to develop their skills to pursue their career in Big Data development would benefit from
What You Will Learn
OS Concepts and Shell Scripting on Linux, Logic Building and Algorithms, Basic Java Programming, Database Fundamentals, SQL and NoSQL Databases, Object Oriented Programming with Java, Fundamentals of Web Technology, Scripting
with Python, Software Engineering , Quality & Coding Standards, Introduction to Big Data and Working with Hadoop, Application Development using MapReduce and Java, Advanced Algorithms to implement MapReduce, Data Transfer and Data Handling using Apache Sqoop
and Flume, Workflow Management using Oozie, Big Data Platforms - Hortonworks and GreenPlum, Cloudera's Hadoop, Distribution and Management Tools, Soft skills
Duration: 67 weeks
Commitment: 12 hours per week
6 Hours Self-studies,
6 Hours Classroom time
Prerequisites
Should have knowledge in programming and databases.
Outline
OS Concepts and Shell Scripting on Linux
Brief Description : This module familiarizes the participants with the working commands of Linux and its file system.
Recommended Learning Duration : 10 Hours
Logic Building and Algorithms
Brief Description : This module helps the participants to develop Logic Building and Algorithm concepts.
Recommended Learning Duration : 12 Hours
Basic Java Programming
Brief Description : This module helps the participants to learn the concepts of programming using Java.
Recommended Learning Duration: 40 Hours
Database Fundamentals and SQL Databases
Brief Description : This module covers the concepts of Databases and SQL.
Recommended Learning Duration: 20 Hours
Object Oriented Programming with Java
Brief Description : This module covers the concepts of OO analysis and design using Java.
Recommended Learning Duration: 40 Hours
Fundamentals of Web Technologies
Brief Description : This module covers the fundamental concepts of Web Designing using HTML, Javascript, etc.
Recommended Learning Duration: 16 Hours
Scripting with Python
Brief Description : This module covers the concepts of Python scripting language and its usage in developing Big Data Algorithms.
Recommended Learning Duration : 4 Hours
Software Engineering , Quality & Coding Standards
Brief Description : This module covers the concepts of engineering a software.
Recommended Learning Duration : 32 Hours
Advanced Algorithms
Brief Description : This module covers the concepts of designing advanced algorithms to implement mapreduce programs.
Recommended Learning Duration: 10 Hours
No SQL Databases
Brief Description : This module covers the concepts of NoSQL databases and their implementation.
Recommended Learning Duration: 40 Hours
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
Application Development using MapReduce and Java
Brief Description : This module covers the programming concept of mapreduce using Java.
Recommended Learning Duration: 20 Hours
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
Workflow Management using Oozie
Brief Description : This module covers the concepts of handling workflows using OOzie.
Recommended Learning Duration : 10 Hours
Big Data Platforms - Hortonworks and GreenPlum
Brief Description : This module deals with the Big data frameworks.
Recommended Learning Duration: 10 Hours
Cloudera's Hadoop Distribution and Management Tools
Brief Description : This module deals with Cloudera framework of Hadoop.
Recommended Learning Duration: 10 Hours
Project
Brief Description : This module is used to guide and hand hold the candidates for developing a project in Big Data Development.
Recommended Learning Duration: 10 Hours
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.
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