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LinkedIn Learning

Advance Your Skills in the Hadoop/NoSQL Data Science Stack

via LinkedIn Learning Path

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Overview

The ecosystem of data science tools based on the Hadoop and NoSQL stack is a crucial and growing part of the future of the industry. Data engineers need a broad knowledge of the components of this platform, and this learning path enables learners to dig in and skill up.
  • Extend your general Hadoop knowledge.
  • Branch into related tools such as Kafka, HBase, Hive, and Cassandra.
  • Build your NoSQL skills.

Syllabus

Courses under this program:
Course 1: Analyzing Big Data with Hive
-Learn how to use Hive to analyze large datasets and derive information from Hadoop. Learn how to work with tables, structures, aggregations, clauses, functions, and more.

Course 2: Advanced NoSQL for Data Science
-Explore the fundamentals of NoSQL. Learn the differences between NoSQL and traditional relational databases, discover how to perform common data science tasks with NoSQL, and more.

Course 3: Cloud Hadoop: Scaling Apache Spark
-Generate genuine business insights from big data. Learn to implement Apache Hadoop and Spark workflows on AWS.

Course 4: Apache Kafka Essential Training: Building Scalable Applications
-Learn about the scalability and manageability aspects of Apache Kafka and how to build asynchronous applications with Kafka and Java.

Course 5: Hadoop for Data Science Tips, Tricks, & Techniques
-Get up to speed with Hadoop. Learn tips and tricks for doing data science work in this popular big data platform.

Course 6: NoSQL Data Modeling Essential Training
-Get started with data modeling for NoSQL databases and learn how to work with common design patterns.

Course 7: Cassandra Data Modeling Essential Training (2017)
-Learn about the architecture of Cassandra—a popular NoSQL database capable of handling large amounts of fast-changing data—and discover how to design Cassandra data models.

Courses

Taught by

Ben Sullins, Dan Sullivan, Lynn Langit, Kumaran Ponnambalam and Robert Van Cleave

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