Advanced Methods in Data Science and Big Data Analytics

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  • Official Curriculum & Courseware Content.
  • Online Interactive Lab's Access.
  • Adaptive e-Learning with trainer's support.
  • Access Class via PC, Mobile App or on a large screen.
  • Attend Live HD Training Sessions via Go To MeetingTM. Interact with trainer and peers like in a real classroom via voice, video conference and live chat.

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.

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.

Course Curriculum

Course # : 96865
Exam : Advanced Methods in Data Science and Big Data Analytics

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