Hadoop and Spark Fundamentals Specialization

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Hadoop and Spark Fundamentals Specialization

Get Started With Hadoop and Spark. Core components, tools, installation, and data processing for the Apache Hadoop Big Data ecosystem.

Instructor: Pearson

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3 course series

Get in-depth knowledge of a subject

Intermediate level

Recommended experience

4 weeks to complete

at 5 hours a week

Flexible schedule

Learn at your own pace

3 course series

Get in-depth knowledge of a subject

Intermediate level

Recommended experience

4 weeks to complete

at 5 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Install, configure, and operate Hadoop and Spark environments on both single machines and clusters, utilizing tools like Ambari and Zeppelin for effective management and development.
Understand and apply core big data concepts, including HDFS, MapReduce, PySpark, HiveQL, and advanced data ingestion techniques using Flume and Sqoop.
Develop, run, and debug data analytics applications, leveraging higher-level tools and scripting languages to efficiently process and analyze large datasets.

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Taught in English

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Specialization - 3 course series

Gain practical, hands-on experience installing and running Hadoop and Spark on your own desktop or laptop, and progress to managing real-world cluster deployments. Through engaging lessons and interactive examples, you’ll master essential concepts such as HDFS, MapReduce, PySpark, HiveQL, and data ingestion tools, while also learning to leverage user-friendly interfaces like Ambari and Zeppelin to streamline analytics workflows and cluster administration. By the end of this course, you’ll possess the foundational skills and confidence to begin your journey in big data analytics and explore the vast Hadoop ecosystem.

Applied Learning Project

Run Apache Pig, Hive, Flume, Sqoop, Oozie, Spark applications and write basic MapReduce/Spark programs. The steps for easily installing a working Hadoop/Spark system on a desktop/laptop and on a local stand-alone cluster using the powerful Ambari GUI are also included. All software used is open source and freely available.

Hadoop and Spark Fundamentals: Unit 1

Course 16 hours

What you'll learn

Understand the core concepts of Hadoop, including its architecture, data lake metaphor, and the role of MapReduce and Spark in big data analytics.
Install and configure a full-featured Hadoop and Spark environment on your desktop or laptop using the Hortonworks HDP sandbox.
Navigate and utilize the Hadoop Distributed File System (HDFS), including advanced features like high availability and federation.
Gain hands-on experience running Hadoop and Spark applications, preparing you for real-world data analytics challenges.

Skills you'll gain

Category: Distributed Computing

Category: File Systems

Category: Linux Commands

Category: Data Lakes

Category: Data Processing

Category: Linux

Category: Software Installation

Category: Data Management

Category: Apache Spark

Category: Apache Hadoop

Category: Big Data

Hadoop and Spark Fundamentals: Unit 2

Course 26 hours

What you'll learn

Understand and implement Hadoop MapReduce for distributed data processing, including compiling, running, and debugging applications.
Apply advanced MapReduce techniques to real-world scenarios such as log analysis and large-scale text processing.
Utilize higher-level tools like Apache Pig and Hive QL to streamline data workflows and perform complex queries.
Gain hands-on experience with Apache Spark and PySpark for modern, scalable data analytics.

Skills you'll gain

Category: Apache Spark

Category: PySpark

Category: Java Programming

Category: Distributed Computing

Category: Big Data

Category: Data Mapping

Category: Apache Hadoop

Category: Apache Hive

Category: Text Mining

Category: Data Processing

Category: Scripting Languages

Category: Debugging

Hadoop and Spark Fundamentals: Unit 3

Course 37 hours

What you'll learn

Master advanced data ingestion techniques into Hadoop HDFS, including Hive, Spark, Flume, and Sqoop.
Develop and run interactive Spark applications using the Apache Zeppelin web interface.
Install, monitor, and administer Hadoop clusters with Ambari and essential command-line tools.
Utilize advanced HDFS features such as snapshots and NFS mounts for enhanced data management.

Skills you'll gain

Category: Command-Line Interface

Category: Data Integration

Category: Configuration Management

Category: Data Processing

Category: Relational Databases

Category: Apache Spark

Category: File Systems

Category: Big Data

Category: Data Pipelines

Category: Software Installation

Category: Data Import/Export

Category: Apache Hive

Category: Apache Hadoop

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Instructor

Pearson

166 Courses1,712 learners

Offered by

Pearson

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Frequently asked questions

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.