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Big data is transforming industries, and this specialization equips you with the skills to succeed. You’ll gain a foundation in Hadoop and Spark, learning how to store, process, and analyze massive datasets. Through theory and hands-on projects, you’ll develop practical expertise that applies directly to real-world scenarios.
You’ll begin with Hadoop, setting up the Hortonworks Sandbox and working with HDFS, MapReduce, Pig, Hive, and Spark. Then, you’ll move to Apache Spark with Scala, mastering RDDs, SparkSQL, DataFrames, and cluster optimization.
Next, you’ll explore Spark Streaming to process live data with use cases like Twitter analysis and log tracking. The specialization concludes with Apache Kafka, where you’ll implement producers, consumers, and advanced operations such as KRaft mode and Kafka Java programming.
This intermediate specialization is designed for learners with basic programming in Java, Python, or Scala. It is ideal for data engineers, developers, and aspiring data scientists.
By the end of the specialization, you will be able to design big data pipelines, process batch and real-time data, and integrate Kafka for scalable applications.
Applied Learning Project
Learners will implement hands-on projects such as querying datasets with Hive, building Spark pipelines, analyzing live Twitter streams with Spark Streaming, and designing scalable Kafka producers and consumers. These projects simulate real-world challenges in big data engineering and analytics.
