Basics of R Software for Data Science

Basics of R Software for Data Science, available at $19.99, has an average rating of 4.45, with 8 lectures, 4 quizzes, based on 96 reviews, and has 1281 subscribers.

You will learn about Understand the Basic Fundamentals, Installation and use of R software. Use of R as a calculator and Functions. Working with Data Frames. Descriptive Statistics-Primary tools which gives first hand information. Graphical tools-various types of plots. Graphical as well as analytical tools. This course is ideal for individuals who are UG students of Science and Engineering. or Students of humanities with basic mathematical and statistical background can also do it. or Working professionals in analytics can also do it. or High School and UG/PG CSE/CS/IT students and anyone who wishes to learn basic statistical data analysis. It is particularly useful for UG students of Science and Engineering. or Students of humanities with basic mathematical and statistical background can also do it. or Working professionals in analytics can also do it. or High School and UG/PG CSE/CS/IT students and anyone who wishes to learn basic statistical data analysis.

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Summary

Title: Basics of R Software for Data Science

Price: $19.99

Average Rating: 4.45

Number of Lectures: 8

Number of Quizzes: 4

Number of Published Lectures: 8

Number of Published Quizzes: 4

Number of Curriculum Items: 12

Number of Published Curriculum Objects: 12

Original Price: ₹1,199

Quality Status: approved

Status: Live

What You Will Learn

Understand the Basic Fundamentals, Installation and use of R software.
Use of R as a calculator and Functions.
Working with Data Frames.
Descriptive Statistics-Primary tools which gives first hand information.
Graphical tools-various types of plots.
Graphical as well as analytical tools.

Who Should Attend

UG students of Science and Engineering.
Students of humanities with basic mathematical and statistical background can also do it.
Working professionals in analytics can also do it.
High School and UG/PG CSE/CS/IT students and anyone who wishes to learn basic statistical data analysis.

Target Audiences

UG students of Science and Engineering.
Students of humanities with basic mathematical and statistical background can also do it.
Working professionals in analytics can also do it.
High School and UG/PG CSE/CS/IT students and anyone who wishes to learn basic statistical data analysis.

R is an open source software – a well organized and sophisticated package – that facilitates data analysis, modelling, inferential testing and forecasting. It is a user friendly software which allows to create new function commands to solve statistical problems. It runs on a variety of UNIX platforms (and similar systems such as LINUX), Windows and Mac OS.
R is the most preferred open-source language for analytics and data science. At Microsoft, R is used by its data scientists, who apply machine learning to data from Bing, Azure, Office, and the Sales, Marketing, and Finance departments. Twitter has been using R for measuring user-experience. On the other hand, the cross-platform compatibility of R and its capacity to handle large and complex data sets make it an ideal tool for academicians to analyze data in their labs.
R can be used for simple calculations, matrix calculations, differential equations, optimisation, statistical analysis, plotting graphs, etc. Also, it is useful to anybody who wishes to undertake extensive statistical computations and data visualization.
Any data analysis is incomplete without statistics. After getting the data, any statistical analysis starts with descriptive statistics which aims to extract the information hidden inside the data. The tools of descriptive statistics are based on mathematical and statistical functions which are to be evaluated using the software. The statistical software are paid as well as free. Most of the statistical software are paid software. A popular free statistical software is R.
What are the basic tools of descriptive statistics and how to use the R software for descriptive statistical analysis is the objective of the course to be taught.

Course Curriculum

Chapter 1: Basic Fundamentals

Lecture 1: Basic Fundamentals, Installation and use of R software

Lecture 2: Use of R as a calculator and Functions

Chapter 2: Matrices and Data Frames

Lecture 1: Matrices and Matrix Operations

Lecture 2: Data Frames

Chapter 3: STATISTICAL FUNCTIONS-1

Lecture 1: Frequencies and Partition values

Lecture 2: Graphics and Plots

Chapter 4: STATISTICAL FUNCTIONS-2:

Lecture 1: Central Tendency and Variation

Lecture 2: Boxplots and Bivariate Plots

Instructors

Prof R Madana Mohana
Professor, Artificial Intelligence and Data Science

Rating Distribution

1 stars: 0 votes
2 stars: 0 votes
3 stars: 10 votes
4 stars: 24 votes
5 stars: 62 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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