Description
Course Modules
1. Introduction to Big Data
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What is Big Data? (Volume, Velocity, Variety, Veracity)
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Big Data challenges & use cases
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Hadoop vs. Traditional Databases
2. Hadoop Fundamentals
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Hadoop Architecture (HDFS & YARN)
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Hadoop Cluster Setup (Single & Multi-node)
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Hadoop Distributed File System (HDFS)
3. MapReduce & YARN
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MapReduce Programming Model
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Writing & Executing MapReduce Jobs
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YARN Resource Management
4. Hadoop Ecosystem Tools
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Apache Hive (Data Warehousing & SQL-like Queries)
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Apache Pig (Data Flow Language)
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Apache Sqoop & Flume (Data Ingestion)
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Apache HBase (NoSQL Database)
5. Apache Spark for Big Data Processing
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Spark Architecture (RDDs, DataFrames)
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Spark SQL, Streaming, MLlib
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Spark vs. Hadoop MapReduce
6. Data Processing & Analytics
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Real-time Data Processing with Kafka
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Data Visualization with Tableau/Power BI
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Big Data Analytics Use Cases
7. Capstone Project
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End-to-end Big Data project (ETL, Analysis, Reporting)
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Industry case studies & best practices
Key Features
✔ Hands-on labs & assignments
✔ Industry-aligned curriculum
✔ Certification exam & project evaluation
✔ Placement assistance & resume guidance
Who Should Enroll?
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Aspiring Data Engineers & Big Data Developers
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IT Professionals transitioning to Big Data
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Software Engineers & Analysts
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Students pursuing careers in Data Science
Certification
Upon completion, participants receive a Certificate in Big Data & Hadoop, validating their expertise in Hadoop ecosystem tools.
Career Opportunities
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Big Data Engineer
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Hadoop Developer
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Data Analyst
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Cloud Data Specialist
