Packt
Big Data Foundations with Hadoop and Spark Specialization
Packt

Big Data Foundations with Hadoop and Spark Specialization

Master Big Data with Hadoop and Spark. Learn Hadoop, Spark, Scala, and Kafka to process, analyze, and stream massive datasets in real time.

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Get in-depth knowledge of a subject
Intermediate level

Recommended experience

1 month at 10 hours a week
Flexible schedule
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Get in-depth knowledge of a subject
Intermediate level

Recommended experience

1 month at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers

What you'll learn

  • Install and configure Hadoop and Spark to manage large-scale datasets effectively.

  • Apply Scala and Spark to build, query, and optimize complex big data pipelines.

  • Process and analyze real-time streaming data using Spark Streaming.

  • Implement Kafka producers, consumers, and advanced operations for scalable solutions.

Overview

What’s included

Shareable certificate

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Taught in English
Recently updated!

September 2025

20 practice exercises

Advance your subject-matter expertise

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from Packt

Specialization - 4 course series

What you'll learn

  • Remember Hadoop setup and configuration steps.

  • Understand the Hadoop ecosystem, including HDFS, MapReduce, and YARN.

  • Apply queries using Pig, Hive, and Spark.

  • Evaluate Hadoop cluster performance and optimize it.

Skills you'll gain

Real Time Data, System Design and Implementation, MongoDB, Apache Kafka, NoSQL, Data Processing, Apache Hive, Big Data, Apache Spark, Databases, SQL, Apache Hadoop, Scalability, and Distributed Computing

What you'll learn

  • Design and implement advanced Spark applications tailored to complex data processing needs.

  • Develop and execute Spark scripts to process large datasets and stream real-time data.

  • Compare and optimize Spark algorithms for better performance in big data applications.

  • Assess machine learning models' effectiveness using Spark MLlib for accurate predictions.

Skills you'll gain

Apache Spark, Scala Programming, Distributed Computing, Graph Theory, Big Data, Real Time Data, Build Tools, Performance Tuning, Data Processing, Development Environment, Regression Analysis, Applied Machine Learning, Data Transformation, and IntelliJ IDEA

What you'll learn

  • Identify key components of the Spark and Scala development environment.

  • Explain the core concepts of Scala and Spark, including Resilient Distributed Datasets (RDDs) and windowing mechanisms.

  • Differentiate between various data integration techniques with Spark Streaming, such as Kafka, Flume, and Cassandra.

  • Assess the performance and reliability of Spark Streaming applications in production environments.

Skills you'll gain

Apache Spark, Apache Kafka, Real Time Data, Application Deployment, Apache Cassandra, Distributed Computing, Apache Hadoop, Scala Programming, Data Processing, Big Data, Development Environment, and Applied Machine Learning

What you'll learn

  • Explain the architecture and core concepts of Apache Kafka.

  • Set up a personal Kafka development environment.

  • Develop Java applications to produce and consume messages in Kafka.

Skills you'll gain

Apache Kafka, Performance Tuning, Apache, Enterprise Application Management, Command-Line Interface, Data Pipelines, Configuration Management, Java, and Real Time Data

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Instructor

Packt - Course Instructors
Packt
1,038 Courses248,073 learners

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Packt

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