R programming from Scratch & Practice Case Studies workout
4.3 (25 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
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R programming from Scratch & Practice Case Studies workout

Analytics / Data Science: Learn to Import, Sort, Merge, Subset, Append, Freq, Univariate, Regression, Derive variable
4.3 (25 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
388 students enrolled
Last updated 5/2017
English
Price: $20
30-Day Money-Back Guarantee
Includes:
  • 2.5 hours on-demand video
  • 1 Article
  • 23 Supplemental Resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Import / Enter / Viewing data and metadata in R
  • Conduct Frequency Distribution Analysis / Univariate Analysis in R
  • Create derived variables
  • Merge / Append data sets
  • Sort / Subset data sets
  • Learn to substring variables
  • Create cross tab analysis
  • conduct Linear Regression analysis
View Curriculum
Requirements
  • This is a basic course
  • intermediary computer skills required to install R, R studio and run commands seeing it on video
Description

What is this course about?

This course helps student learn R syntax for

  • Import / Enter / Viewing data and metadata in R
  • Conduct Frequency Distribution Analysis / Univariate Analysis in R
  • Create derived variables
  • Merge / Append data sets
  • Sort / Subset data sets
  • Learn to substring variables
  • Create cross tab analysis
  • conduct Linear Regression analysis
  • Practice case studies

Terminology associated with the course

  • R syntax
  • Data Mining
  • Analytics
  • Machine Learning

Material for the course

  • 20 HD Videos
  • Excel Data sets
  • PDF of presentation
  • R code

How long the course should take?

Approximately 4 hours to internalize the concepts

How is the course structures

Section 1 - explains how to get R, R Studio, Understand environment and data for workout

Section 2 - explains the R syntax through examples

Section 3 - explains some other syntax needed for working

Section 4 - Practice Case Studies - apply your knowledge to solve business problems

Why take this course?

This course ensure quick learning in a simplified way. It explains the most important aspects of working on data and conduct analysis through example.

Who is the target audience?
  • Those who wants to learn basic R programming with Example
  • Those who know SAS and know wants to know, how to get the same analysis done in R
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Curriculum For This Course
Expand All 42 Lectures Collapse All 42 Lectures 03:16:54
+
Getting Started with R
7 Lectures 11:52

Welcome Note
01:06


Installation of R and R studio / Understand R environment
03:42

Please download associated excel files. This should be available in right side download section

Preview 01:29

Download files used in the course
02:39

Section PDF
11 pages
+
Work with Data
11 Lectures 43:22

Please download the R code using right side download area. You should practice along with the course to master the syntax.

Import Data in R
06:52

Direct data entry in R
05:43

View Data and Metadata
05:48

Frequency Distribution Analysis
03:20

Numeric Variable Analysis / Univariate Analysis
06:14

Merge Data sets
03:04


Derive New Variables
07:21

Arithmetic and Logical Operators
01:37

Section PDF
27 pages
+
Other R procedure
6 Lectures 14:26

Filter data, Keep some fields, drop some fields, sort data and show top n rows
07:18


Regression Analysis
01:46

Using Substring Function
02:13

Section PDF
15 pages
+
Practice Case Studies - apply your knowledge to solve business problems
18 Lectures 01:14:17


A: Find new in list B (B-A) stuff
09:19

Q: Variable Substring Challenge
02:21

A: Variable Substring Challenge
08:31

Q: Investigate linear relationship between variables
02:26

A: Investigate linear relationship between variables
12:04


A:Tabular report in presence of two class variable & different statistics neede
02:45

Little help about seasonality and pair T test for next problem
00:42

Q: Pair T Test in presence of seasonality
02:14

A: Pair T Test in presence of seasonality
03:29

If you need to refresh yourself about chi square test of independence, please
refer to this link https://www.youtube.com/watch?v=IrZOKSGShC8

Q: Calculate red car percentage for different age group and run chi square test
02:50

A: Calculate red car percentage for different age group and run chi square test
13:29

Q: Calculate relative variance (Coefficient of Variance)
00:58


A: Calculate relative variance (Coefficient of Variance)
01:20

Closing Words
00:50
About the Instructor
Gopal Prasad Malakar
4.1 Average rating
1,091 Reviews
15,749 Students
14 Courses
Credit Card Analytics Professional - Trains on Data Mining

I am a seasoned Analytics professional with 16+ years of professional experience. I have industry experience of impactful and actionable analytics. I am a keen trainer, who believes that training is all about making users understand the concepts. If students remain confused after the training, the training is useless. I ensure that after my training, students (or partcipants) are crystal clear on how to use the learning in their business scenarios. My expertise is in Credit Card Business, Scoring (econometrics based model development), score management, loss forecasting and MS access based database application development.