Hadoop for Developers Training is a practical, hands-on program designed to equip learners with the skills required to develop scalable big data applications using the Hadoop ecosystem. This training focuses on HDFS operations, MapReduce programming, data processing workflows, Hadoop ecosystem tools integration, and building efficient data pipelines. Participants will gain real-world experience in developing distributed applications that process large-scale datasets in batch processing environments.

Participants will gain strong development skills in Hadoop ecosystem, enabling them to build scalable data processing applications, implement MapReduce jobs, and handle large-scale datasets efficiently.

• Java Developers and Software Engineers
• Big Data Developers and Data Engineers
• Backend Developers working with large datasets
• IT Professionals transitioning into Big Data development
• Students and professionals entering Hadoop ecosystem

• Basic knowledge of Java programming
• Understanding of data structures and algorithms fundamentals
• Familiarity with Linux/Unix command line
• Basic understanding of databases and data concepts

• Hadoop architecture and ecosystem understanding
• HDFS file system operations and data handling
• MapReduce programming and job development
• Data processing and batch computation techniques
• Integration with Hadoop ecosystem tools
• Debugging and optimizing Hadoop jobs
• Building scalable distributed data processing applications

Upon completion of this training, participants will be able to develop distributed data processing applications using Hadoop. They will be capable of writing MapReduce programs, managing large datasets in HDFS, and building scalable batch processing solutions for big data environments.

Introduction to Hadoop Development Environment
• Overview of Hadoop architecture and components
• Setting up Hadoop development environment
• HDFS commands and file system operations
• Data storage and retrieval concepts

HDFS Programming and Data Handling
• Reading and writing data in HDFS
• File formats and data ingestion basics
• Data replication and fault tolerance concepts
• Working with large datasets
MapReduce Programming Fundamentals
• Introduction to MapReduce programming model
• Mapper and Reducer implementation
• Job configuration and execution
• Input and output formats

Advanced Hadoop Development Concepts
• Job optimization techniques
• Debugging MapReduce applications
• Introduction to Hive and Pig integration
• Real-world batch processing use cases

• Hadoop architecture and HDFS operations
• MapReduce programming model
• Mapper and Reducer implementation
• Job execution and optimization
• Data ingestion and file handling
• Batch processing workflows

• Hands-on MapReduce coding exercises
• HDFS data handling assignments
• Practical job execution tasks
• Mini project on batch data processing pipeline

Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.

Participants who successfully complete the training will receive an AcadNXT Certification in Hadoop for Developers Training, validating their expertise in Hadoop development, MapReduce programming, HDFS data processing, and distributed application development.