R Programming for Data Science for Absolute Beginners

R Programming for Data Science for Absolute Beginners, available at $54.99, has an average rating of 4.45, with 66 lectures, 14 quizzes, based on 13 reviews, and has 1548 subscribers.

You will learn about R programming from Beginning to Advance. Data Visualizations using ggplot and Base plots When , which and how to plot for Inferences Learn to plot scatter , bar chart , histograms, time-series Create and access R objects – vectors,list,factors, dataframes , matrices Learn to write conditions, loops and functions Upload real world data like bank marketing data with 45,000 records This course is ideal for individuals who are Beginners who are looking to enhance their data science skills It is particularly useful for Beginners who are looking to enhance their data science skills.

Enroll now: R Programming for Data Science for Absolute Beginners

Summary

Title: R Programming for Data Science for Absolute Beginners

Price: $54.99

Average Rating: 4.45

Number of Lectures: 66

Number of Quizzes: 14

Number of Published Lectures: 66

Number of Published Quizzes: 14

Number of Curriculum Items: 80

Number of Published Curriculum Objects: 80

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

R programming from Beginning to Advance.

Data Visualizations using ggplot and Base plots

When , which and how to plot for Inferences

Learn to plot scatter , bar chart , histograms, time-series

Create and access R objects – vectors,list,factors, dataframes , matrices

Learn to write conditions, loops and functions

Upload real world data like bank marketing data with 45,000 records

Who Should Attend

Beginners who are looking to enhance their data science skills

Target Audiences

Beginners who are looking to enhance their data science skills

**** Reviews****

I m gaining great new skills with this course. I had no exp in R , now I m gaining confidence . Recommended for the beginners– Myint Htoo

**** Lifetime access to course materials . 100% money back guarantee ****

If you are an absolute beginners in R , then this is the place .

Learn R program right from the basic to intermediate and advance level.

Learn how to do data visualizations on all kind of data sets.

Create and access various R datatypes and objects like vectors,factors and dataframes.

Create your own functions , loops and conditions.

Work on various plots : scatter , box plots , histograms, bar charts and derive the business and actionable insights.

Upload real world data like bank marketing data with 45,000 records

Create and access R objects – vectors,list,factors, dataframes , matrices

Do various mathematical operations on dataframes , vectors , list and other R objects.

When , which and how to plot for Inferences

Learn to write conditions, loops and functions

Case Study Include:

Identify which customers are eligible for credit card issuance

-> Use R functions , loops and apply R knowledge gained to resolve the real world problem

Root Cause Analysis of Uber Demand Supply Gap

->Understand business problems.

->Upload Uber Datasets ( drop time, pickup time, driver ID , destination , pickup point )

->Do the data visualizations and find the various insights from the datasets

-> Prepare PPT for the company CEO and other stakeholders.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Welcome to the Course

Lecture 2: Introduction to the Course

Lecture 3: Installation of R and R Studio

Lecture 4: Understanding R Studio

Lecture 5: Understanding Datatypes in R

Lecture 6: Crash Course in R – 1

Lecture 7: Crash Course in R – 2

Lecture 8: Crash Course in R – 3

Lecture 9: Introduction to Vectors

Lecture 10: Vectors in R – 1

Lecture 11: Vectors in R – 2

Lecture 12: Factors in R -1

Lecture 13: Factors in R -2

Lecture 14: Introduction to Matrices

Lecture 15: Matrices

Chapter 2: Dataframes in R

Lecture 1: Introduction to Dataframes

Lecture 2: Creating Dataframes

Lecture 3: Accessing Dataframes

Lecture 4: Operations in Dataframes

Lecture 5: File Upload into Dataframe

Lecture 6: Introduction to List

Lecture 7: List

Lecture 8: Summary

Chapter 3: Constructs in R programming

Lecture 1: Introduction to Constructs in R

Lecture 2: Relational and Logical Operators

Lecture 3: Conditional Statements

Lecture 4: Understanding Bank File for Credit Card

Lecture 5: Writing Conditions for Credit Card Issuance

Lecture 6: Loops

Lecture 7: Loops-2

Lecture 8: Introduction to Functions

Lecture 9: Functions – Built-in

Lecture 10: Create Your own Functions

Lecture 11: Sapply Functions

Lecture 12: Summary

Chapter 4: Visualizations in R

Lecture 1: Introduction to the world of Visualization

Lecture 2: R base Plots-1

Lecture 3: R base Plots-2

Lecture 4: Introduction to ggplot

Lecture 5: Getting Started with ggplots

Lecture 6: Scatter Plots Using ggplot

Lecture 7: Plotting values on ggplot in Scatter plots

Lecture 8: ggplot on Large Datasets

Lecture 9: ggplot as Object

Lecture 10: Plotting Bar Charts using ggplot

Lecture 11: Jitters in ggplot

Lecture 12: Dodge Plots

Lecture 13: Histograms using ggplot

Lecture 14: Timeseries Plots

Lecture 15: Summary

Chapter 5: Case Study- Uber Demand Supply Gap

Lecture 1: Understanding Business Problem

Lecture 2: Uber Datasets

Lecture 3: Data Analysis – 1

Lecture 4: Data Visualisations -1

Lecture 5: Data Visualisations – 2

Chapter 6: Investment Case Study using Excel : Bonus Lectures

Lecture 1: Introduction to Investment Case Studies

Lecture 2: Understanding Case Studies and Downloads

Lecture 3: Data Preparation-1

Lecture 4: Data Preparation – 2

Lecture 5: Data Preparation – 3

Lecture 6: Data Preparation – 4

Lecture 7: Data Preparation – 5

Lecture 8: Country Wise Analysis

Lecture 9: Investment Type Analysis

Lecture 10: Company Category Type Analysis

Lecture 11: PPT Presentation to Business Users for Data Insights

Instructors

Piyush S | insightEdge100.com
Data Scientist | Data Engineer | Project Manager

Rating Distribution

1 stars: 0 votes

2 stars: 1 votes

3 stars: 0 votes

4 stars: 6 votes

5 stars: 6 votes

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