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What is included in the statistics in R Course?

The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examples. This course is part of multiple programs

What is included in the R specialization?

As the first course in the Specialization, the course provides the essential foundation of R needed for the following courses. We cover basic R concepts and language fundamentals, key concepts like tidy data and related "tidyverse" tools, processing and manipulation of complex and large datasets, handling textual data, and basic data science tasks.

What do the lectures on R data science cover?

The lectures cover topics such as reading data from SPSS and spreadsheets and using packages for advanced R functions. In addition to this, learn to create charts and plots, check statistical assumptions and reliability of the data. End the lessons with lectures on how to share the data insights with the help of presentations, web pages and graphs.

What are the benefits of completing the R console course?

Upon completing this course, learners will have fluency at the R console and will be able to create tidy datasets from a wide range of possible data sources. Reset deadlines in accordance to your schedule.

What are the courses R?

In summary, here are 10 of our most popular r coursesData Science: Foundations using R: Johns Hopkins University.Data Analysis with R: Duke University.Data Analysis with R Programming: Google.R Programming: Johns Hopkins University.Data Visualization & Dashboarding with R: Johns Hopkins University.More items...

What are the prerequisites for R?

Below are the prerequisites for learning R programming:You must know of the basics of any programming language. ... You should have a deep knowledge of statistics and mathematics.You must have a good understanding of graphs and plots that are used for data visualization.More items...

Is there any R certification?

R is now considered one of the most popular analytics tools in the world. In this certificate program you will develop the skill set necessary to perform key aspects of data science efficiently.

What fields is R used in?

Some of the important applications of R Programming Language in the domain of Data Science are:Finance. Data Science is most widely used in the financial industry. ... Banking. ... Healthcare. ... Social Media. ... E-Commerce. ... Manufacturing.

Does R require coding?

This made R more user-friendly for individuals without a programming background. We strongly recommend that you install RStudio in addition to R, as it will make your life exponentially easier.

Is R better than Python?

Python Vs R: Full Comparison R is a statistical language used for the analysis and visual representation of data. Python is better suitable for machine learning, deep learning, and large-scale web applications. R is suitable for statistical learning having powerful libraries for data experiment and exploration.

Where should I learn R?

10 Best Online courses to learn R Programming for Beginners and Experienced Programmers in 2022R Programming A-Z™: R For Data Science With Real Exercises! ... R Programming for Statistics and Data Science 2022. ... R Programming by Johns Hopkins [Coursera] ... Learn R from Scratch [Educative]More items...

What is an R skill?

R is a versatile, open source programming language that was specifically designed for data analysis. R is extremely useful for data management, statistics and analyzing data.

How quickly can I learn R?

If you have experience in any programming language, it takes 7 days to learn R programming spending at least 3 hours a day. If you are a beginner, it takes 3 weeks to learn R programming.

What jobs can I get if I know R?

The careers in R Programming that can lead to your 'R' enlightenment is as below:R programmer.Data Scientist.Data Analyst.Data Architect.Data Visualization Analyst.Geo Statisticians.Database Administrator.Quantitative Analysis with R.

What kind of jobs can I get with R?

What jobs can I obtain with the R programming language?Data Scientist.Data Architect.Geo Statisticians.R programmer.Quantitative Analysis with R.Data Visualization Analyst.Data Analyst.

Is R useful in finance?

Finance. Data Science is most widely used in the financial industries. R is the most popular tool for this role. This is because R provides an advanced statistical suite that is able to carry out all the necessary financial tasks.

What is R Programming Language?

R is a programming language and free software environment for statistical computing and graphics supported by the R Foundation for Statistical Comp...

Why learn R?

We recommend these courses for those with some basic knowledge of R that want to use it in a Data Science and Software Development context. You may...

What jobs use R?

According to Burning Glass, there were ~50K job postings in the last 12 months requiring R as a skill. Some of the functional job titles requiring...

What skills or experience do I need to already have, before starting to learn R?

While there are generally no specific prerequisites for beginner-level R courses, programming language basics is one of the key topics you typicall...

What kind of people are best suited for roles in R?

People who are highly analytical and curious are typically best suited for roles in R. People who enjoy statistics and using statistical models to...

What are common career paths for someone in R?

Some common career paths for people in R include machine learning engineers, data scientists, data miners, data engineers, and statisticians. These...

What topics can I study that are related to R?

Mathematics, statistics, and AI are topics you could study that are related to R. Data visualization is another related topic, along with probabili...

About this Course

In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language.

Offered by

The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.

Week 1: Background, Getting Started, and Nuts & Bolts

This week covers the basics to get you started up with R. The Background Materials lesson contains information about course mechanics and some videos on installing R. The Week 1 videos cover the history of R and S, go over the basic data types in R, and describe the functions for reading and writing data.

Week 2: Programming with R

Welcome to Week 2 of R Programming. This week, we take the gloves off, and the lectures cover key topics like control structures and functions. We also introduce the first programming assignment for the course, which is due at the end of the week.

Week 3: Loop Functions and Debugging

We have now entered the third week of R Programming, which also marks the halfway point. The lectures this week cover loop functions and the debugging tools in R. These aspects of R make R useful for both interactive work and writing longer code, and so they are commonly used in practice.

Week 4: Simulation & Profiling

This week covers how to simulate data in R, which serves as the basis for doing simulation studies. We also cover the profiler in R which lets you collect detailed information on how your R functions are running and to identify bottlenecks that can be addressed. The profiler is a key tool in helping you optimize your programs.

About this Course

This course provides a rigorous introduction to the R programming language, with a particular focus on using R for software development in a data science setting.

Offered by

The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.

Data Manipulation

During this module, you'll learn to summarize, filter, merge, and otherwise manipulate data in R, including working through the challenges of dates and times.

Text Processing, Regular Expression, & Physical Memory

During this module, you'll learn to use R tools and packages to deal with text and regular expressions. You'll also learn how to manage and get the most from your computer's physical memory when working in R.

Large Datasets

In this final module, you'll learn how to overcome the challenges of working with large datasets both in memory and out as well as how to diagnose problems and find help.

About the Mastering Software Development in R Specialization

R is a programming language and a free software environment for statistical computing and graphics, widely used by data analysts, data scientists and statisticians. This Specialization covers R software development for building data science tools.

The Analytics Edge

What you’ll learn: An applied understanding of many different analytics methods, including linear regression, logistic regression, CART, clustering, and data visualization. How to implement all of these methods in R. An applied understanding of mathematical optimization and how to solve optimization models in spreadsheet software.

Analyzing Big Data with Microsoft R Server

Learn how to use Microsoft R Server to analyze large datasets using R.

R Programming

In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language.

Data Analysis with R

Exploratory data analysis is an approach for summarizing and visualizing the important characteristics of a data set.

Analyzing Big Data in R using Apache Spark

Master Apache Spark, a popular cluster computing framework used for performing large scale data analysis. SparkR provides a distributed data frame API that enables structured data processing with a syntax familiar to R users.

Introduction to R

With over 2 million users worldwide R is rapidly becoming the leading programming language in statistics and data science. Every year, the number of R users grows by 40%, and an increasing number of organizations are using it in their day-to-day activities.

Forecasting using R

Forecasting involves making predictions about the future.

About this Course

This course covers advanced topics in R programming that are necessary for developing powerful, robust, and reusable data science tools. Topics covered include functional programming in R, robust error handling, object oriented programming, profiling and benchmarking, debugging, and proper design of functions.

Offered by

The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.

Reviews

Brilliant course. Loved Week 4 for OOP. This was really new for me and would love to have been able to see its application in real world examples to better cement the concepts.

About the Mastering Software Development in R Specialization

R is a programming language and a free software environment for statistical computing and graphics, widely used by data analysts, data scientists and statisticians. This Specialization covers R software development for building data science tools.

1. R Programming Certification by Johns Hopkins University (Coursera)

This course will teach you how to program in R and use it for effective data analysis. It also covers reading data into R, accessing R packages, writing R functions, debugging and commenting R code. It is taught by Roger D.

2. Data Science: R Basics Certificate by Harvard University (edX)

It is a fact that in recent years R has become one of the most sought after languages that can be used in an array of fields. This course is designed to introduce you to the basics of R programming. Learn the key concepts by solving a problem that involves a real dataset.

3. Statistics with R Certification by Duke University (Coursera)

This Statistics specialization is created by Duke University and taught by Mine Çetinkaya-Rundel, Associate Professor; David Banks, Professor; Colin Rundel, Assistant Professor and Merlise A Clyde, Professor.

4. Software Development in R Certification by Johns Hopkins University (Coursera)

Get trained rigorously in the R language with this certification course by Johns Hopkins University. Understand how to handle complex data, build R packages and develop custom data visualizations. It has been developed and taught by Roger D.

5. Programming for Data Science with R Nanodegree Certification (Udacity)

R is becoming one of the most popular programming languages in the IT industry, especially in the data science field. If you’re also among those who want to make a career in the Data Science field, then this course is the right fit for you.

6. R Training Course Online (LinkedIn Learning)

In this course Instructor, Barton Poulson introduces you to the statistical processing language R. Commence with installing R on your computer before going ahead with the lessons. The lectures cover topics such as reading data from SPSS and spreadsheets and using packages for advanced R functions.

8. Data Science and Machine Learning Bootcamp with R (Udemy)

Jose Marcial Portilla has an MS from Santa Clara University and comes with years of experience as a developer and instructor in data science and programming. In one of his best courses, he will teach you how to use R for data science, machine learning and data visualization.