Advanced Methods in Data Science and Big Data Analytics|

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Advanced Methods in Data Science and Big Data Analytics

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Course Description

About the Course

This course builds on skills developed in the Data Science and Big Data Analytics course. The main focus areas cover Hadoop (including Pig, Hive, and HBase), natural language processing, social network analysis, simulation, random forests, multinomial logistic regression, and data visualization. With a technology-neutral approach, this course utilizes several open-source tools to address big data challenges.

Course Curriculum

Course # : 96865

Advanced Methods in Data Science and Big Data Analytics

Exam : Advanced Methods in Data Science and Big Data Analytics

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Advanced Methods in Data Science and Big Data Analytics

Objectives

MapReduce functionality
NoSQL databases and Hadoop Ecosystem tools for analyzing large-scale, unstructured data sets
Natural language processing, social network analysis, and data visualization concepts
Use advanced quantitative methods, and apply one of them in a Hadoop environment
Apply advanced techniques to real-world datasets in a final lab

Target Audience

Aspiring data scientists
Data analysts that have completed the associate level Data Science and Big Data Analytics course
Computer scientists wanting to learn MapReduce and methods for analyzing unstructured data such as text.

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