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Business Analytics Professional – R An Overview

Discover the power of R for data analytics. From data mining to big data analytics, R offers extensive capabilities for organizing, analyzing, and visualizing data. Learn how R integrates with other software and why it's the choice of top data scientists.

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Business Analytics Professional – R An Overview

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  1. Business Analytics Professional – R An Overview

  2. Agenda ADMISSIONS COVERAGE OVERVIEW USP BAP - R APPENDIX: ImarticusOverview Faculty Profiles Visiting Faculties Sample Learning Material Online Learning Portal

  3. Why R? Data mining has entered its golden age. R is the weapon of choice for legions of data scientists! What are the reasons for its sudden popularity? Cost of Ownership Versatility R is an open source software that is free to download. R is perhaps the only analytics software to run on MAC. Customizable Data scientists can improve the software’s code or write variations for specific tasks. A Data Scientists’ Dream R offers extensive analytics capabilities ranging from Text Analytics, Predictive, Time Series, Optimization. Integration R is particularly useful in data analytics because it contains a number of built-in mechanisms for organizing data, running calculations on the information and creating graphical representations of data sets. Some people familiar with R describe it as a supercharged version of Microsoft’s Excel spreadsheet software that can help illuminate data trends more clearly than is possible by entering information into rows and columns. • Integrates with other software vendors: SAS, Oracle, IBM, Teradata, TIBCO, Alteryx, SAP. • Integration with HDFS, WEKA, Python, MATLAB. • R & Excel: RExcel is an add in for Microsoft Excel, allowing access to the statistics package R from within Excel. Rattle GUI is widely for data mining. Big Data Analytics made possible by Revolution Analytics (Commercial version of R)

  4. Why R? (Contd.) • Growing faster than any other data science language • 70% of data miners use R • Highest Paid IT Skill • Rexer Survey, • Oct 2013 • Dice Survey, • Jan 2014 • KDNuggetsSurvey, Aug 2013 • Ranked #15 of all programming languages • Most-used data science language after SQL • RedMonk rankings, Jan 2014 • O’Reilly Survey, • Jan 2014 Companies Already Onboard R R is the #1 Google Search for Advanced Analytics software Google Trends, March 2014 FDA John Deere Lloyds of London & Many More… Facebook Google Twitter Foursquare ANZ Bank More than 2 million users worldwide. Oracle Estimate, Feb 2012 Demand for R language skills is on the rise. R You Ready for R?

  5. Overview of BAP-R The Business Analytics Professional – R (BAP-R) is a comprehensive, short-term program that provides aspirants with a thorough understanding of R programming language for effective data analytics. • KEY FOCUS AREAS • The program provides insights into: • Statistics using R • Predictive, Text and Multivariate Analytics • Optimization • Forecasting • OBJECTIVE • To gain practical knowledge of R language as a tool for effective data analysis, which will enable aspirants to apply the learnings in their respective careers. Learning Methodology Program Options Program Duration • The learning is divided into two levels: • Basic Analytics using R (Foundational) • Advanced Analytics using R (Advanced) Instructor-led classroom training using a combination of lectures by experienced faculty, case studies and live project work, managed by a fully integrated online learning portal. BAP-R is a short-termweekend course lasting 3 months • Basic Level: 1.5 Months • Advanced Level: 1.5 Months

  6. Program Overview In this program, you will learn how to program in R and how to use R for effective data analysis. The program is divided into two levels: Basics and Advanced. Level 1 – Basic Analytics Using R Module 1: R Basics Module 2: Statistics using R Module 3: Functions in R Module 4: Review & Evaluation 60 Hours over 1.5 Month Level 2 – Advanced Analytics Using R Soft Skills & Mock Interviews • 120+ • Hours Module 1: Predictive Analytics Module 2: Text Analytics Module 3: Multivariate Analysis • OF LEARNING TO GET YOU • JOB READY FOR A CAREER IN BUSINESS ANALYTICS! Module 4: Optimization Module 5: Forecasting 60 Hours over 1.5 Months

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