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This comprehensive Big Data and Hadoop course is designed for beginners and aspiring data engineers looking to gain in-depth knowledge of the Big Data ecosystem. The course starts with the basics of Big Data, Hadoop, and their applications, moving on to HDFS architecture, MapReduce, YARN, and core components of the Hadoop ecosystem.
You’ll learn data ingestion, processing, and analytics using Hive, Pig, HBase, Sqoop, and Kafka, along with hands-on Hadoop cluster setup, installation, and administration. The course also covers real-world use cases, data engineering workflows, and ETL processes, and dives into Big Data tools and technologies like Spark, Storm, Cassandra, MongoDB, and Impala.
Intermediate lessons guide you on data visualization, analytics using Python and R, and integrating Big Data pipelines, preparing you for interview questions, certifications, and practical projects. By the end, learners will be equipped with the skills to become a proficient Big Data engineer, work with distributed systems, and handle large-scale data processing efficiently.