Big Data Hadoop Certification Training Course

Course Overview

• Course Duration:2 Months (Including Lab Work, Internship, and real-world assignment).
• Modes of Training: Online Classes/Offline Training (at selected centers).
• Projects:Available – Real-world Big Data and Hadoop projects.

Big Data Certification – Professional Training Course

• Understand the fundamentals of Big Data and the Hadoop ecosystem.
• Learn HDFS architecture, MapReduce programming, and cluster management.
• Perform large-scale data analysis using Hive, Pig, and Spark.
• Integrate data from multiple sources using Sqoop and Flume.
• Optimize Hadoop performance and manage real-time analytics workflows.
• Prepare for globally recognized Big Data Hadoop credential preparation Exams.

Overview of Big Data Certification Course

The Big Data Hadoop credential preparation Training Course is designed for data professionals, analysts, and engineers who want to gain expertise in handling massive datasets. The program provides a deep understanding of Hadoop's architecture and its powerful data processing tools, providing you with the specialized technical expertise needed to advance your career in the data-driven world.

Through real-world case studies and hands-on lab exercises, you'll learn to store, process, and analyze big data efficiently. By the end of this course, you'll be ready to earn your Big Data Hadoop credential preparation and pursue careers in Data Engineering, Analytics, or Business Intelligence.

1. Introduction to Big Data and Hadoop

• Understanding Big Data.
• Hadoop Ecosystem and Architecture.

2. Hadoop Distributed File System (HDFS)

• Blocks and replication.
• HDFS commands and architecture.
• NameNode, DataNode and Secondary Node.

3. MapReduce Programming

• Writing and executing MapReduce jobs.
• Input and output formats.
• Hive architecture and Query Language.
• Data transformation and querying.
• Data transfer using Sqoop.
• Ingesting real-time data with Flume.
• Introduction to HBase.
• HBase architecture and operations.
• Integrating HBase with Hive and MapReduce.

7. Final Project & Internship

• Industry-based case study real-world assignment.
• Internship support and mentorship.
• In-depth Hadoop and Big Data training.
• Hands-on lab sessions and real-time data projects.
• Tools: HDFS, MapReduce, Hive, Pig, Sqoop, HBase.
• Cloud-based infrastructure for practice.
• Career readiness training and resume building.
• Business Intelligence Engineer.
• Experience real-world applications of Hadoop tools by working on live projects involving massive datasets, helping you understand hands-on challenges in Big Data environments.
• Gain expertise in the complete Hadoop framework including MapReduce, Hive, Pig, Sqoop, Flume, and HBase—skills sought after by top MNCs.
• Train on simulated Hadoop clusters via cloud environments to develop scalable and production-ready big data solutions without needing physical hardware.
• Receive internship support and career outcome guidance along with resume building, interview preparation, and career counseling by experienced professionals.