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Course Detail

Course Name R Programming Lab (Data Science)
Course Code 19EAC385
Program B. Tech. in Electronics and Computer Engineering
Year Taught 2019

Syllabus

R types and classes, Functions, Data Structures, Reading and writing Data from files, Variables, Control Structures. Input Output, Graphics, Data Visualization, Simulation-Generating Random Numbers, Setting the random number seed, Simulating a Linear Model, Random Sampling, Data Analysis Case Study.

Objectives and Outcomes

Course Objectives

  • Basically, R is a functional and object-oriented programming language. This means the function is the central element of software and analyses. In this lab course, we deal intensively with writing and testing functions in R.

Course Outcomes

  • CO1: Understanding the types, classes and functions of R Programming.
  • CO2: Accessing and Processing of Data.
  • CO3: Understanding the I/O interface programming.
  • CO4: Study and Analyse Data Visualisation.
  • CO5: Implement any application level simulation using R

CO – PO Mapping

PO/PSO/
CO		 PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12 PSO1 PSO2
CO1 1
CO2 1 2
CO3 1 1 2 1
CO4 1 1 2 1 1
CO5 1 2 3 2 2

Textbook / References

Textbook / References

  • R Programming for Data Science, Roger D Peng, Lean Publication, 2016
  • R for Data Science: Import, Tidy, Transform, Visualize, and Model Data by Hadley Wickham, O’RELLY, 2017
  • Hands-On Programming with R: Write Your Own Functions and Simulations, Garrett Goleman, O’RELLY, 2014 http://cran.r-project.org(link is external)

Evaluation Pattern: 80:20 (Internal: External)

Assessment Internal External
*Continuous Assessment (CA) 80 –
End Semester – 20
*CA – Can be Quizzes, Assignment, Projects, and Reports.

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