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R Programming & Big Data Analytics
Unit 2: R Fundamentals (PDF Format)
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Unit 2: R Fundamentals (PDF Format)
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Unit 2 - R Fundamentals - LN -Final 2- 28.06.18.compressed.pdf
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◄ Unit Summary
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Course Learning Objectives
Course Structure
Course Assessment
Course Pedagogical Card
Announcements
Unit 1: Setting up the Environment - Getting R Ready (PDF Format)
Self-Learning Activity
References & Further Readings
Unit Summary
Learning Activity 1: Working with Variables
Submission Box: Learning Activity 1 - Working with Variables
Learning Activity 2: Vectors and Matrices
Submission Box: Learning Activity 2 - Vectors and Matrices
Learning Activity 3: Arrays
Submission Box: Learning Activity 3 - Arrays
Learning Activity 4: Data Frames and Lists
Submission Box: Learning Activity 4 - Data Frames and Lists
Learning Activity 5: Control Structures and Functions
Submission Box: Learning Activity 5 - Control Structures and Functions
References & Further Readings
Unit Summary
Unit 3: Data Analysis and Visualisation with R (PDF Format)
Learning Activity 1: Reading data from spreadsheets
Customers.csv File
Employee.csv File
Learning Activity 2: Manipulating data frames
Practical Activity: Test data
Learning Activity 3: Descriptive Statistics Measures
Learning Activity 4: Pie Charts
References & Further Readings
Unit Summary
Assignment 1: R script
Cereals.csv File
Unit 4: Big Data Essentials (PDF Format)
Additional Reading Resource: Horton Works
Discussion Forum: Phenomenon of Big Data
Learning Activity 1: Evolution of Big Data
Learning Activity 2: Application of Big Data
References & Further Readings
Unit Summary
Unit 5: Big Data Ecosystem (PDF Format)
Discussion Forum: NameNode and DataNode
Online Quiz - Big Data
Practical Activity: Big Data Ecosystem
References & Further Readings
Unit Summary
Unit 6 - Big Data Analytics (PDF Format)
Lab Activity 1
Lab Activity 2
Practical Activity 1
Practical Activity 2
Practical Activity 3
References & Further Readings
Unit Summary
Assignment 2: Machine Learning Algorithms to predict Diabetes
Learning Activity 1: Working with Variables ►
R Programming & Big Data Analytics
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