INSTRUCTOR LED ONLINE LIVE SESSIONS

Hadoop Ecosystem

Course Brief

How big is BIG? Become a big data expert through an intensive training program customised across various levels designed specifically for you. It will make participants solve real-time problems with huge datasets.Through this intensive program we aim to train the participants in a way that they are prepared to appear for International Certifications The aim of this course is to prepare you for international certification in Hadoop. The HDP Certified Developer (HDPCD) exam is for Hadoop developers proficient in Pig, Hive, Sqoop and Flume. During this course you’ll learn to develop hadoop applications for storing processing and analyzing data stored in Hadoop cluster. The course is mainly categorized into 3 areas:
Data Ingestion (SCOOP and FLUME)
Data Transformation (PIG)
Data Analysis (HIVE)

    Introduction - types of Data Ingestion - Ingesting Batch Data - Ingesting Streaming Data - Examples

    Learning Outcomes:

    • Understanding Data Ingestion.

    Introduction - Sqoop Architecture - Connect to MySQL database - Sqoop - Import - Export - Eval - Joins - exercises.

    Learning Outcomes:

    • Understand Sqoop architecture and uses
    • Able to load real-time data from an RDBMS table/Query on to HDFS
    • Able to write sqoop scripts for exporting data from HDFS onto RDMS tables.

    Introduction - Flume Architecture - Flume master - Flume Agents - Flume Collectors - creation of Flume configuration files - Examples - Exercises

    Learning Outcomes:

    • Understand Flume architecture and uses
    • Able to create flume configuration files to stream and ingest data onto HDFS

    Introduction-Pig Data Flow Engine-Map Reduce Vs. Pig - Data Types-Basic Pig Programming-Modes of execution in PIG-Miscellaneous Commands - Group, Filter, Join, Order, Flatten, cogroup, Flatten, Illustrate, Explain - Parameter substitution- creating simple UDFs in Pig-Examples-Exercises.

    Learning Outcomes:

    • Understand Apache PIG , PIG Data Flow Engine
    • Understand data types, data model, and modes of execution.
    • Able to store the data from a Pig relation on to HDFS.
    • Able to load data into Pig Relation with or without schema.
    • Able to split, join, filter, and transform the data using pig operators
    • Able to write pig scripts and work with UDFs.

    Descriptive Statistics: Introduction - Descriptive Statistics - Central Tendency - Variability - Mean - Median - Range - Variance - Summary Exercises
    Graphics : Introduction - Types - Packages - Basic graph - Histograms - Stem Leaf Graph - Box Plots - Scatter Plots - Bar Plots.

    Learning Outcomes:

    • Understand the importance of Hive, Hive Architecture
    • Able to find the central tendency, summary of given data sets.
    • Understand the importance of graphical output and various graphs.
    • Able to plot various graphs for the given data set.
    • Implement Descriptive Statistics in R.

Mr. P.V.N.Balarama Murthy
Hadoop Map Reduce and Hadoop Ecosystem

Mr. P.V.N.Balarama Murthy, is an M.Tech(CSE) having over 10 years of teaching and technical training experience. He is specialist in Data Science and Bigdata. He has experience in deploying hadoop clusters. As technical trainer, he has trained a number of people in C,C++, Java, Oracle, Hadoop (Administration, Development with MR, PIG, Hive, Flume, Sqoop) and Data Science with R. He has guided to his credit 15+ students to get Hortonworks certifications for Hadoop.

A dedicated, resourceful and result oriented instructor that he is, it is helping shape up careers of students.

Ms. Jyothi SanjeevaMani
Hadoop Ecosystem

Ms. Jyothi SanjeevaMani has over 15 years of satisfying teaching and technical training experience. She is a Research Scholar of Big Data Analytics from a reputed university. As a technical trainer she trained many students in industry oriented subjects like C, C++, Java, MySQL, Oracle (SQL, PL/SQL), Python, Linux, Openstack, BigData - Hadoop(MapReduce, Pig, Hive, Sqoop, Flume), Data Science with both Python and R.

She is an Asst.Professor with the Department of IT at The Keshav Memorial Institute of Technology (KMIT).

She is a dedicated, resourceful and a result oriented instructor, who strives to help students change marginal grades into good grades.

  • Are there any pre requisites for this course?

    Basic knowledge of Java will help.

  • Can I just enroll in a single course? I'm not interested in the entire Specialization?

    No you cannot enroll for individual skill sets within a defined course on teleuniv.

  • How long does it take to complete this Specialization?

    Most learners are able to complete the Specialization in about 3 months.

  • Do I need to take the courses in a specific order?

    We recommend taking the courses in the order presented, as each subsequent course will build on material from previous courses.

  • What will I be able to do upon completing this Specialization?

    This specialization will unlock great career opportunities as a Hadoop developer. Become a Hadoop expert by learning concepts like Pig, Hive, Flume and Sqoop. Get industry-ready with some of the best Big Data projects and real-life use-cases.

  • Can I attend a demo session?

    We have limited number of participants in a live session to maintain the Quality Standards, hence, participation in a live class without enrollment is not possible. However, we can create a demo login for one demo session.

  • What are the payment options?

    You can pay by Credit Card, Debit Card or Net Banking from all the leading banks. We use a Payment Gateway.

  • Do you provide placement assistance?

    Teleuniv is associated with Keshav Memorial Institute of Technology, one among the top performing colleges in Hyderabad and hence lot of recruitment firms contacts us for our students profiles from time to time. Since there is a big demand for this skill, we help our certified students get connected to prospective employers. Having said that, please understand that we don't guarantee any placements however if you go through the course diligently and complete the assignments and exercises you will have a very good chance of getting a job.

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