Analytics foundation & Data science with R

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Rajarajeshwari Nagar, Bangalore

Course ID: 43309

Rajarajeshwari Nagar, Bangalore

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Hayavadan Nargund picture
Hayavadan Nargund

MCA

5 Years of Experience

About Hayavadan Nargund

Highly motivated post graduate in computer applications with 10 years academic experience.
(1) Rajarajeswari College of Engineering Bangalore.
Designation : Asst.Professor

Responsibilities:


19/7/2010 TO till present

i. Working as a full time Asst.Professor in the Dept. of MCA for 7.3 years at RRCE.
ii. Worked as a VTU flying squad Chairman and member.
iii. Worked as a External and Internal examiner for MCA Lab Examination.
iv. Handled subjects like C,C++,CG,SP,JAVA,J2EE,UNIX,ADA,OOMD.
v. Attended seminars, workshops and conferences.
vi. Placement training and transportation coordinator.
vii IBM certification for handling Rational Software and providing training.
viii Member of Indian Society For Technical Education(MISTE).
ix. Serving as a Peer-Coach | Mentor to Students.
x. Guided MCA projects and Evaluated.
xi. Worked as a VTU question paper setter for MCA.
xii. Worked as a resource person for conducting workshop.


(2) DayanandaSagar College of Engineering Bangalore. 21/7/2008 TO 20/2/2010
Designation : Lecturer

Responsibilities:
i. Worked as a full time Lecturer in the Dept. of
MCA(VTU) for 1.7 years at DSCE.
ii. Handled subjects like OOAD,OOMD,OR,C,C++.
iii. In charge of Disciplinary committee.
iv. Managing seminars, workshops and conferences.
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About the Course

Who is this course for?


This tutorial is designed for software programmers, statisticians and data miners who are looking forward for developing statistical software using R programming. If you are trying to understand the R programming language as a beginner, this tutorial will give you enough understanding on almost all the concepts of the language from where you can take yourself to higher levels of expertise.


What will the students learn in this course?


Unit 1: An overview of Data Science and Analytics    


Unit 2: Business Statistics & Applications


Unit 3: An Introduction to R Language and Platform


Unit 4: A Perspective on Big Data Analytics


Unit 5: Predictive models and Machine learning


 Is there anything the students need to bring to the class


 Interest to learn the Data Science concept.


Prerequisites


Before proceeding with this tutorial, you should have a basic understanding of Computer Programming terminologies. A basic understanding of any of the programming languages will help you in understanding the R programming concepts and move fast on the learning track.


 


CASE STUDIES AND PROJECTS


Store Clustering Objective of the study was to create clusters based on certain parameters. There are 515 store spread across Tamil Nadu and Karnataka to identify the buying behavior in these stores. K-Means Clustering technique used in R to analyze data, create cluster profiles and provide recommendations based on cluster profiles


 Car Price Estimation Objective of the study was to run a regression model that will  explain the price of a car as a function of different attributes. Linear Regression modeling technique used in R to analyze and formulate the results.

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