Introduction To Data Science Using R Programming
Introduction To Data Science Using R Programming, available at $19.99, has an average rating of 3.8, with 55 lectures, based on 22 reviews, and has 106 subscribers.
You will learn about Learn core ceoncepts of R programming Learn to visualize data using R Implement Data science concepts using R Implement statistical models using R This course is ideal for individuals who are Any student interetsed in learning Data Science using R will find this course very useful It is particularly useful for Any student interetsed in learning Data Science using R will find this course very useful.
Enroll now: Introduction To Data Science Using R Programming
Summary
Title: Introduction To Data Science Using R Programming
Price: $19.99
Average Rating: 3.8
Number of Lectures: 55
Number of Published Lectures: 55
Number of Curriculum Items: 55
Number of Published Curriculum Objects: 55
Original Price: $29.99
Quality Status: approved
Status: Live
What You Will Learn
- Learn core ceoncepts of R programming
- Learn to visualize data using R
- Implement Data science concepts using R
- Implement statistical models using R
Who Should Attend
- Any student interetsed in learning Data Science using R will find this course very useful
Target Audiences
- Any student interetsed in learning Data Science using R will find this course very useful
A powerful
comprehensive course on mastering data visualization and analytics
using R!
Data
was once only powerful when it came to making business decisions, but
today data plays a more important role and is currently the basis of
all the modern business functions. The growing need for organized
data has resulted in the higher demands for data scientists, miners
and also data analysts.
This
is the prime time to join one of the world’s fastest growing
industry as a data scientist and all you need to become one is this
course!
We
have designed this exceptionally comprehensive course at beginners as
well as intermediate students who want to master the art of data
science and learn exactly how to analyze and organize data to create
charts or graphs. The course
has been dedicated to helping you understand one of the most
important tools of data science – R Statistical Environment.
In
addition to the R environment, you will also go over the popular data
science R programming language. While
there are many other languages that can be used for data science, R
has become synonymous with data analytics and has been used
industry-wide in data science. R refers to the R programming language
as well as R statistical computing environment that is used for
statistical computing and graphics. The R language is popularly used
among statisticians, data miners, data analysts, etc.
This
course focuses on helping breakdown R and R programming language into
simple and easy to understand concepts that cover everything you need
to know to get started with Data Science. The course will not only
help you learn the R language’s basic syntax, but also the
computing environment where you will learn exactly how to import
data, organize the data, create charts and graphs and also export
data.
The
course will in-depth cover topics such as Basic Data Visualization,
Advanced Data Visualization, Generating Maps using JSON Structures,
Implementation of Statistics, Data Munging/Wrangling, Data
Manipulation and so much more!
At
the end of this course, you will have mastered exactly how to work
with data and bend it to your wishes. This
is the perfect course for anyone who is looking to make the jump into
the world of Data Science.
Enroll
now and learn how you can become an expert at data science!
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction
Chapter 2: Basics of R tool
Lecture 1: Introduction to Course
Lecture 2: R programming installation and concepts
Lecture 3: R programming computations
Chapter 3: Basic Data Visualization
Lecture 1: Data Visualization – Module
Lecture 2: Pie charts
Lecture 3: Bar charts
Lecture 4: Boxplots
Lecture 5: Histograms
Lecture 6: Line charts
Lecture 7: Scatterplots
Lecture 8: Case Study Basic data visualization
Chapter 4: Advance Data Visualization
Lecture 1: Advanced Data Visualization
Lecture 2: Basic Illustration of ggplot2 package
Lecture 3: Facetting
Lecture 4: Boxplots and Jittered Plots
Lecture 5: Histograms and Frequency Polygons
Lecture 6: Bar Charts and Time Series
Lecture 7: Basic Plot Types
Lecture 8: Case Study for ggplot2 package Scatterplot Encircling
Lecture 9: Surface Plots
Lecture 10: Revealing uncertainity
Lecture 11: Weighted data
Lecture 12: Drawing Maps- Vector Boundries
Lecture 13: Drawing Maps – Point Metadata
Lecture 14: Diamonds data for research
Lecture 15: Dealing with overlapping
Lecture 16: Statistical summaries
Lecture 17: Scatterplot from excel file
Lecture 18: Heatmap and area chart from excel file
Lecture 19: Various bar charts from excel file
Chapter 5: Leaflet Maps
Lecture 1: Implementing Leaflet with R tool
Lecture 2: Adding Markers in map
Lecture 3: Popups and Labels
Lecture 4: Shiny Framework using Leaflet and R
Chapter 6: Statistics
Lecture 1: Mean, median and mode
Lecture 2: Linear Regression
Lecture 3: Multiple Regression
Lecture 4: Logistic Regression
Lecture 5: Normal Distribution
Lecture 6: Binomial Distribution
Lecture 7: Poisson Regression
Lecture 8: Analysis of Covariance
Lecture 9: Time Series Analysis
Lecture 10: Case study Time Series from dataset
Lecture 11: Decision Tree
Lecture 12: Implementation of decision tree in Dataset
Lecture 13: Nonlinear Least Square
Lecture 14: Case Study- Random Forest
Lecture 15: Survival Analysis
Chapter 7: Data Manipulation
Lecture 1: Case Study Exporting data in R
Lecture 2: Data Munging and Visualization
Lecture 3: Hierarchial Clustering
Lecture 4: K means clustering
Lecture 5: Bonus Lecture: More Interesting Stuff, Offers and Discounts
Instructors
-
Eduonix Learning Solutions
1+ Million Students Worldwide | 200+ Courses -
Eduonix-Tech .
Rating Distribution
- 1 stars: 1 votes
- 2 stars: 2 votes
- 3 stars: 4 votes
- 4 stars: 13 votes
- 5 stars: 2 votes
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