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Data Science Training

Data science program is designed by Data Scientists keeping in mind of upcoming industry requirement and latest trend to fulfill the pool of manpower. It enhance your technical, conceptual as well as the logical approach towards data, which helps you to understand the data as well as to get insights of it.

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Data Science Training

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  1. Data Science Training Let’s Get Started!

  2. Description • Data science program is designed by Data Scientists keeping in mind of upcoming industry requirement and latest trend to fulfill the pool of manpower. It enhance your technical, conceptual as well as the logical approach towards data, which helps you to understand the data as well as to get insights of it.

  3. Objectives • Understand the obligations of a Data Scientist • Research Big Data using R, Hadoop and Machine Learning • Get some answers concerning the methodology related with the Data Analysis Life Cycle • Make sense of how to use data plans including XML, CSV and SAS, SPSS • Change data using best practices and gadgets

  4. Objectives • Make sense of how to complete diverse Data Mining strategies • Grasp the use of machine learning estimations in R • Separate data using Hadoop Mappers and Reducers • Take in the fundamentals of Apache Mahout • Take after acknowledged methods in data recognition and streamlining frameworks

  5. Prerequisites Aspirants opting for this course should have basic knowledge core Java and functional programming, and mathematical aptitude.

  6. This course is appropriate for: This course is ideal for aspirants who are looking to enhance their data analysis understanding, along with Big Data Analytics, Analytics Managers, Data Scientists, Hadoop Professionals, Information Architects and more.

  7. Topics • Introduction to Data Science • Basic Data Manipulation using R • Machine Learning Techniques Using R Part-1 • Machine Learning Techniques Using R Part-2 • Machine Learning Techniques Using R Part-3 • Introduction to Hadoop Architecture • Integrating R with Hadoop • Mahout Introduction and Algorithm Implementation

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