Big Data with Apache Hadoop

This course provides a comprehensive introduction to Apache Hadoop, the open-source framework that enables scalable, distributed processing of massive datasets across clusters of computers. Designed for beginners and intermediate-level learners, the course covers the fundamentals of Big Data, Hadoop’s core components (HDFS, YARN, and MapReduce), and explores the broader Hadoop ecosystem, including Hive, Pig, HBase, Sqoop, and Oozie.

Through hands-on labs, real-world case studies, and a capstone project, participants will learn how to set up and manage a Hadoop environment, write data processing jobs, query large datasets, and build end-to-end Big Data workflows. By the end of the course, learners will have the practical skills to process, store, and analyze large volumes of structured and unstructured data using Hadoop tools.

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🎯 Learning Outcomes

By completing this course, learners will be able to

Understand the challenges of Big Data and how Hadoop addresses them

Set up and configure a Hadoop environment (locally or in the cloud)

Database Management

Store and retrieve data using HDFS

Write and execute MapReduce programs for large-scale data processing

Use Hive for SQL-like querying on large datasets

Develop data pipelines with Pig, and work with NoSQL databases using HBase

Import/export data between Hadoop and RDBMS using Sqoop

Automate workflows with Oozie

Understand how Apache Spark integrates with Hadoop (optional module)

Build and present a real-world Big Data project

🛠️ Course Features

100% practical and
project-based learning

Real-world
capstone projects

Code reviews and
mentor support

Resume and GitHub
portfolio development

Lifetime access to
course materials (if online)

Certification upon
successful completion

🧑‍💻 Who Should Enroll

🔧 Prerequisites

📚 Hadoop Course Content

Module 1: Introduction to Big Data & Hadoop

What is Big Data?
5 V’s of Big Data (Volume, Velocity, Variety, Veracity, Value)
Traditional systems vs. Big Data systems
Introduction to Apache Hadoop
Hadoop Ecosystem Overview
Real-world use cases of Hadoop

Module 2: Hadoop Architecture and Components

Hadoop Architecture Overview
HDFS (Hadoop Distributed File System)
NameNode, DataNode
Block size, Replication factor
YARN (Yet Another Resource Negotiator)
ResourceManager, NodeManager
Job scheduling
Anatomy of a Hadoop job

Module 3: Setting Up Hadoop

Hadoop installation modes
Local
Pseudo-distributed
Fully-distributed
Installing and configuring Hadoop on Linux (Ubuntu/CentOS)
Running HDFS and YARN services
Basic HDFS commands and file operations

Module 4: MapReduce Programming

Introduction to MapReduce paradigm
InputFormat, OutputFormat, Mapper, Reducer classes
Writing MapReduce programs in Java
Running and debugging jobs
Advanced concepts
Combiner, Partitioner, Counters
Performance tuning

Module 5: Apache Hive

What is Hive? When to use it?
Hive Architecture and Components
HiveQL vs SQL
Creating databases and tables
Loading and querying data
Partitions and Bucketing
UDFs (User Defined Functions)

Module 6: Apache Pig

Module 7: Apache HBase

Introduction to NoSQL and HBase
Deployment Preparations & Environment Variables
HBase Architecture: HMaster, RegionServer, Zookeeper
Row key design and schema modeling
CRUD operations in HBase shell
Integrating HBase with MapReduce

Module 8: Data Ingestion with Sqoop and Flume

📦 Apache Sqoop

🔄 Apache Flume:

Module 9: Workflow Scheduling with Apache Oozie

Module 10: Introduction to Apache Spark (Optional Advanced Module)

Module 11: Hadoop on Cloud (AWS EMR / GCP Dataproc)

Module 12: Capstone Project

🧪 Assessments & Hands-On

💼 Land job at your dream company

🪪 Course Certificate

Showcase your certificate as symbol of couse copliation

Official & Verified

Ideal for fast-paced learning with daily live sessions and hands-on projects

Easily Shareable

Suitable for working professionals or students balancing other commitments

Enhance Credebility

Suitable for working professionals or students balancing other commitments

Better Opportunities

Suitable for working professionals or students balancing other commitments

Industry Leading Placement

Whether you're aspiring to become a full-stack developer, looking to enhance your career, or build your own end-to-end applications, this

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