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NoSQL, Big Data, and Spark Foundations Specialization

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Course Features

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Duration

4 months

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Beginner

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Effort

2 hours per week

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Teaching Type

Self Paced

Course Description

In the data management field, Big Data Engineers and NoSQL-skilled professionals are highly in demand. This specialization is for people who want to learn the fundamental skills needed for working with Big Data and Apache Spark. The three courses are packed with information and cover the most popular NoSQL databases, Apache Cassandra and MongoDB, as well as Apache Spark, which is an analytics engine that allows for large-scale data processing. After a brief overview of the various NoSQL data repositories (not just SQL), you will be able to work with many of them, including MonogoDB, Cassandra, IBM Cloudant and MonogoDB. You will perform data management tasks such as inserting, updating and deleting data, creating and replicating databases, querying, indexing, aggregated & sharding it, and querying. You'll then gain a basic understanding of Big Data technologies like Hadoop, MapReduce and HDFS. Next, you will learn more about Apache Spark, Spark Dataframes and Spark SQL. Finally, you will be able to scale Spark with Kubernetes and the Spark Application UI. The final course will teach you how to use Spark Structured Streaming SparkML for extract, transform and load processing (ETL) as well as machine learning tasks. This specialization is for those who are just starting out in NoSQL or Big Data, whether they are a Data Engineer, Software Developer or IT Architect.

Course Overview

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International Faculty

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Instructor-Moderated Discussions

Skills You Will Gain

What You Will Learn

Develop foundational knowledge of Big Data and gain hands-on lab experience using Apache Hadoop, MapReduce,  Apache Spark, Spark SQL, and Kubernetes

Develop hands-on NoSQL experience working with MongoDB, Apache Cassandra, and IBM Cloudant

Perform Extract, Transform and Load (ETL) processing and Machine Learning model training and deployment with Apache Spark

Work with NoSQL databases to insert, update, delete, query, index, aggregate, and shard/partition data

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