Programming (R) Course Outline PDF
Document Details
Uploaded by PrestigiousKineticArt
Indian Institute of Management Indore
Arnab Koley
Tags
Summary
This document provides a course outline for a Programming (R) course at the Indian Institute of Management Indore. It covers topics such as vectors, matrices, data frames, programming structures, and data importing/exporting/visualization, and details evaluation components and installation steps. The course is part of an Executive Post Graduate Diploma in Management and Artificial Intelligence program.
Full Transcript
Executive Post Graduate Diploma in Management and Artificial Intelligence Course Outline Course Title: Programming (R) No of Sessions: 10 Course Instructor: Prof. Arnab Koley Instructor Prof. Arnab Koley E-mail [email protected]...
Executive Post Graduate Diploma in Management and Artificial Intelligence Course Outline Course Title: Programming (R) No of Sessions: 10 Course Instructor: Prof. Arnab Koley Instructor Prof. Arnab Koley E-mail [email protected] Course Objectives: To introduce concepts of R programming language. Pedagogy: Using R programming language Learning Outcomes: To have a working knowledge of R. Evaluation: Category Particulars Percentage Homework / End Term 100% Evaluation components (minimum two required) Total 100% Reference Book (if any): Remarks for participants: Participants should install R and RStudio Desktop on their laptop before the course begins. The following steps may be helpful to complete the installations. Step-1: Download and install R from https://cran.r-project.org/bin/windows/base/ (for Windows) or https://cran.r-project.org/bin/macosx/ (for macOS). Step-2: Download and install RStudio Desktop from https://posit.co/download/rstudiodesktop/. Session-wise plan: Session No. Description On-line Mode 1-2. Topic(s): Vector and Matrix Learning Objective(s): To work with vectors and matrices. Session Objective: To create vectors and matrices. Reading(s): Instructor’s notes Case(s): None 3. Topic(s): Data frame Learning Objective(s): To work with data frames. Session Objective: To create data frames. Reading(s): Instructor’s notes Case(s): None 4-5. Topic(s): Programming Structures Learning Objective(s): To write loop, conditional statements. Session Objective: To write loops and conditional statements. Reading(s): Instructor’s notes Case(s): None 6. Topic(s): Data importing and exporting. Learning Objective(s): To import and export data files. Session Objective: To understand how data files are imported to and exported from R. Reading(s): Instructor’s notes Case(s): None Topic(s): Graphical Display of data 7. Learning Objective(s): Data visualization. Session Objective: To visualize data through graphs, plots, charts. Reading(s): Instructor’s notes Case(s): None Topic(s): Measure of central tendency and dispersion of data 8. Learning Objective(s): Computations of basic statistics. Session Objective: To measure central tendency and dispersion of data. Reading(s): Instructor’s notes Case(s): None Topic(s): Writing customized function. 9-10. Learning Objective(s): To learn how to create function and use of packages. Session Objective: To learn writing customized functions and the use of packages. Reading(s): Instructor’s notes Case(s): None
