Course Highlights

    • 12 Hours of Recorded Sessions
    • Concepts Explained in Kannada
    • Industrial projects
    • Real-life Case Studies
    • Quizzes & Assignments
    • Doubt Clarification
    • Telegram Community Access
    • Completion Certificate
    • Become an Alumni of MicroDegree
    • Unlimited access*
  • Who Should Attend

    • Freshers and Early Professionals
    • Experienced Professionals
  • Job Opportunities

    • BigData Analyst
    • Data Engineering
    • Data Analyst
    • Step towards Analytics

Completion Certificate by MicroDegree

On completion of course become a proud alumni of MicroDegree. MicroDegree is chosen among top innovative startups by Government of Karnataka's flagship Elevate Call-2 program

Course curriculum

  • 1

    Introduction

    • Introduction to Big Data

    • Join Developer Community

  • 2

    Introduction to Hadoop Ecosystem

    • What is Cluster, Node, RACK?

    • Hadoop Services

    • NameNode and Secondary NameNode

    • Hadoop File read, write and distribution

    • Job Tracker and Task Tracker

    • YARN Resource Manager (> Hadoop 2.0)

    • Hadoop Installation

    • How do you feel about the course till Now ?

  • 3

    Unix Basics

    • UNIX and User, Group Creation

    • Directories and Files operation commands1

    • Directories and Files operation commands2

    • File and Directory Permission

    • Variables and Arrays

    • Conditions and Loops

    • Functions

    • Shell Scripting explained with File Watcher Usecase

    • Student Feedback

  • 4

    HDFS

    • What is HDFS | HDFS Command Line | HDFS Commands Listing | Working with HDFS Directories

    • HDFS File Operations Commands Part1

    • HDFS File Operations Commands Part2

    • HDFS File Operations Commands Part3

    • HDFS File Operations Commands Part4

    • HDFS Project : File Watcher Script

  • 5

    Map-Reduce

    • Map-Reduce Introduction

    • Map-Reduce Architecutre Explained (Record Reader, Mapper, Sort and Shuffling, Reducer)

    • Mapper Explained with Example Part1

    • Mapper Explained with Example Part2

    • Reducer Explained with Example Part1

    • Reducer Explained with Example Part2

    • Driver Explained with Example and Jar Build

    • Map Only WordCount Job Execution

    • Map-Reduce WordCount Job Execution

    • Combiner Explained with Example

    • Partitioner Explained with Example

    • Assignments and Notes

  • 6

    HIVE

    • Hive and its Architecture

    • HIVE Installation

    • Hive Connection and Databases creation

    • Primitive DataTypes

    • Table creation and SELECT

    • LOAD data into tables

    • Types of Tables and Difference

    • Collection DataTypes with Example Part1

    • Collection DataTypes with Example Part2

    • Partitions and its Types

    • Static Partitioning with Example

    • Dynamic Partitioning with Example

    • Limitations of HIVE Partitions

    • Static Partitioning with Example

    • Dynamic Partitioning with Example

    • Limitations of HIVE

    • Bucketing and Uses

    • Bucketing with Example

    • InBuilt Date Functions

    • InBuilt Mathematical Functions

    • InBuilt Collection Functions

    • InBuilt Aggregate Functions

    • InBuilt Table Generating Functions

    • User Defined Functions (UDF)

    • File Formats Part1 - Text, Sequence and AVRO

    • File Formats Part2 - RC, ORC and Parquet

    • Hive Indexes and View with Example

    • ACID Transactions

    • Hive Queries: Order By, Group By, Distribute By, Cluster By Examples

    • Hive Join & SubQuery Tutorial with Examples

    • Join Methods and Performance

    • Performance Improvement Techniques

    • Project 1 : Sentiment Analysis

    • Project 2: Aviation Data Analytics

    • Student Feedback

  • 7

    OOZIE

    • Oozie Introduction

    • Installation of Apache Oozie

    • Oozie Workflow, Coordinator and Property files

    • Job Scheduling with Example Part1

    • Job Scheduling with Example Part2

  • 8

    Sqoop

    • Sqoop Introduction and Features

    • Sqoop Import with Example

    • Sqoop Export with Example

    • Sqoop Eval with Example

    • Sqoop Delta Import with Example

    • Sqoop Jobs

  • 9

    Capstone Project

    • End to End Project 1

    • End to End Project 2

Expert Instructor

 Abhimanyu

BigData Engineer

Abhimanyu has 12+ Years of industry experience in building enterprise data applications and ETL pipelines at scale. He has worked across Telecom, Banking, Insurance, and Retail domains with top companies. Has expertise in Big Data Technologies, Python, Scala, and BI tools like Tableau, Power BI. He recommends big Data skills as vital for Data Engineers.

Learner Review

  • Akshata Kothari

    Thank you so much for this course. The concepts explained by the trainer was really good and clear. As it was in kannada it helped me in understanding the concept better.

  • karthik k

    You are giving examples for every concept which makes us learn faster. Excellent. Keep going

  • Chethana Amin

    It's really a good thought to start a course in kannada. It helps lot of people.

  • Divya G

    Explaining in Kannada is understanding in good manner

  • Deepashree N

    Awesome thing... u guys made python very very easy which can be learnt in our mother tongue.... thank you...

  • Monica Govindappa

    Learning in Kannada is helping out to grasp things quickly over all making it to learn in an interesting way.

Refer & Earn

Friends ಗೆ Refer ಮಾಡಿರಿ ಹಾಗೂ ಪಡೆಯಿರಿ Cash upto ₹15,000