Go Back   2023 2024 Courses.Ind.In > Main Category > Main Forum > Sathyabama Institute of Science and Technology B.E. - Automobile Engineering SCSA400

Thread: Sathyabama Institute of Science and Technology B.E. - Automobile Engineering SCSA400 Reply to Thread
Your Username: Click here to log in
Title:
  
Message:
Trackback:
Send Trackbacks to (Separate multiple URLs with spaces) :
Post Icons
You may choose an icon for your message from the following list:
 

Additional Options
Miscellaneous Options

Topic Review (Newest First)
September 23rd, 2020 04:52 PM
ReenaK
Sathyabama Institute of Science and Technology B.E. - Automobile Engineering SCSA400

Sathyabama Institute of Science and Technology B.E. - Automobile Engineering SCSA4001 R Programming Syllabus

SATHYABAMA INSTITUTE OF SCIENCE AND TECHNOLOGY

SCSA4001 R PROGRAMMING

UNIT 1 INTRODUCTION TO R 9 Hrs.
History and fundamentals of R, Installation and use of R / R Studio / R Shiny, Installing R packages, R – Nuts and Bolts -
Getting Data In and Out –Objects in R -Arrays,DataFrame and List -Control Structures and Functions- Loop Functions-Data
Manipulation- String Operations- Matrix Operations.

UNIT 2 R DATA INTERFACES 9 Hrs.
CSV Files, XSL files, XML files, Web Data- Data Preprocessing: Missing Values, Outliers ,Principle Component Analysis -
Data Visualization – Charts & Graphs-Pie Chart, Bar Chart, Box plot, Histogram, Line graph, Scatter Plot.

UNIT 3 STATISTICAL MODELING IN R 9 Hrs.
Descriptive statistics-R Packages: Regression (MASS package) - Distribution (STATS package) - ANOVA - Time Series
Analysis.

UNIT 4 MACHINE LEARNING IN R 9 Hrs.
Classification: Decision Trees, Random Forest, SVM – Clustering: K-Means, Fuzzy - Association Rule Mining - Outlier
Detection.

UNIT 5 BUILDING R SHINY APPLICATION 9 Hrs.
User Interface, Control Widgets, Dynamic Output - R Hadoop: Installation of RHadoop-rhdfs –rmr2-Data Analysis with
RHadoop- Case Study.
Max. 45 Hrs.


COURSE OUTCOMES
On completion of the course, student will be able to
CO1 - List motivation for learning R programming language
CO2 - Access online resources for R and import new function packages into the R workspace
CO3 - Import, review, manipulate and summarize data-sets in R
CO4 - Explore data-sets to create testable hypotheses and identify appropriate statistical tests
CO5 - Perform appropriate statistical tests using R
CO6 - Create and edit visualizations with R


TEXT / REFERENCE BOOKS
1. Hands-On Programming with R: Write Your Own Functions and Simulations By Garrett Grolemund, O'Reilly Media,
Inc., 2014.
2. R for Data Science, Hadley Wickham, Garrett Grolemund,"O'Reilly Media, Inc.2016.
3. Introduction to Statistics and Data Analysis - With Exercises, Solutions and Applications in R By Christian Heumann,
Michael Schomaker and Shalabh, Springer, 2016
4. The R Software-Fundamentals of Programming and Statistical Analysis -Pierre Lafaye de Micheaux, Rémy Drouilhet,
Benoit Liquet, Springer 2013
5. A Beginner's Guide to R (Use R) By Alain F. Zuur, Elena N. Ieno, Erik H.W.G. Meesters, Springer 2009


END SEMESTER EXAMINATION QUESTION PAPER PATTERN
Max. Marks: 100 Exam Duration: 3 Hrs.
PART A: 10 Questions of 2 marks each-No choice 20 Marks
PART B: 2 Questions from each unit with internal choice, each carrying 16 marks 80 Marks

Posting Rules
You may post new threads
You may post replies
You may not post attachments
You may not edit your posts

BB code is On
Smilies are On
[IMG] code is On
HTML code is Off


All times are GMT +5.5. The time now is 11:14 AM.


Powered by vBulletin® Version 3.8.7
Copyright ©2000 - 2024, vBulletin Solutions, Inc.
Search Engine Friendly URLs by vBSEO 3.6.1
vBulletin Optimisation provided by vB Optimise (Lite) - vBulletin Mods & Addons Copyright © 2024 DragonByte Technologies Ltd.