What is R programming?

R programming is the most widely and very famous programming language. It is specifically used for

Machine learning

Artificial Intelligence

Data analysis

Data visualization

R is known as the best programming language in the field of Data sciences and is commonly used by any type of statistician. It possesses a complete catalog of statistical and graphical methods. The extensive library of tools in the R catalog serves as the best way to analyze data and visualize it in any complex graph. For most of the complex and informative graphs you see, there is a huge chance that R is behind them.

Benefits of R programming:

R is an extensive library of various statistical and graphical approaches. It offers Linear, non-linear modeling, Time-series, spatial analysis, Statistical tests, Clustering platforms, classification, and much more techniques.

The most beneficial function of R programming is the graphic analysis of data and its representation in high-end graphs. Those graphs are of publication quality and represent many mathematical symbols also. Many interactive graphics are offered through additional packages.

R is also a very useful programming language and offers many extensible features and techniques to help developers in programming.

R programming plays an important role in

Artificial Intelligence

Data cleaning

Data preparation

Machine learning

Most of the foreign and big companies like Google, Uber, Facebook, etc who handle a lot of data use R programming language for many functionalities.

What is Artificial Intelligence?

Artificial intelligence (AI) refers to intelligence shown by machines rather than natural intelligence produced by animals such as humans. Leading AI textbooks define the discipline as the study of intelligent agents, which are any systems that sense their surroundings and take actions to increase their chances of attaining their objectives.

However, prominent AI researchers reject this definition, which uses the term "artificial intelligence" to denote robots that simulate cognitive capabilities that humans connect with the human mind, such as "learning" and problem-solving. Advanced web search engines, recommendation systems (like those used by YouTube, Amazon, and Netflix), understanding human speech (like Siri and Alexa), self-driving cars (like Tesla), automated decision-making, and competing at the highest level in strategic game systems are all examples of AI applications (such as chess and Go). The AI effect is a phenomenon that occurs when robots grow more competent and jobs deemed to need intelligence are eliminated from the definition of AI. Optical character recognition, for example, is typically left out of AI discussions despite the fact that it has become a commonplace technique.

It is a computer science strategy for teaching computers to understand and emulate human communication and behavior. Based on the data given, Artificial Intelligence has created a new intelligent machine that thinks, responds, and executes activities much like people. Artificial intelligence (AI) is capable of doing highly technical and specialized activities such as robotics, speech and picture recognition, natural language processing, and problem-solving, among others. The application of AI may be employed in research and development fields all around the world, thanks to the ever-expanding expansion of Computer Science. Artificial intelligence is not the same as human intellect, but it can learn and think like humans, and in the future, it may surpass it.

Why should you learn R?

An R programmer in India earns Rs 5 million per anum as an average base salary and can also earn up to Rs 9 million per anum.

Many big companies like Google, Facebook, and uber also hire R programmers and offers very high pay. If you are an R programmer you can be hired as a Data Scientist and Business Analyst. R programmers are in very high demand in Startup companies.

R programming has a wide range scope as well as it can also be used by business experts to grow their businesses.

The best feature of R programming is Graphics which can be used in any field to get benefits. It is very easy to use and gives you a high output. R programming language is a very flexible and best scripting language and offers you the best resource bank. R has a big community that helps programmers and data scientists a lot.

R is the best language for data analysis because it offers programmers an enormous number of packages and many usable tests and formulas for Data analysis. R is also useful for parallel computation.

Why we should use R for AI programming?

R is one of the most efficient and effective tools for statistical data analysis and manipulation. Furthermore, R is both affordable and attractive.

R is a data analytics platform that may be used for a variety of purposes. While it may not be the quickest language for every application, it is extremely fast and can assist with practically every AI activity imaginable:

R AI Pros

Datasets should be collected and cleaned up.

To process the data, employ matrix transformations and linear algebra.

Divide a huge dataset into training and test sets at random.

Use a variety of statistical and machine learning functions.

Provide an appraisal of the results' dependability and goodness of fit.

Use the results to make predictions about fresh data.

Keep an eye out for changes in the nature of the incoming data.

The complete development process may be represented in a markdown document to enable the dissemination of discoveries and new strategies identified.

The language has been adapted for use in large data situations.

The language can even give an experimental web interface for users to try their hand at data analysis, resulting in a synergy between man and machine to handle big data challenges.

While the R language offers a few novel ways of completing standard tasks, a lot of work can be accomplished with only a little code written in an interactive environment. This makes it simple to create and test new ideas, as well as to validate them using the large variety of visual features available.

On top of that, this innovative tool is free, operates on common and server hardware, employs an open-source interpreter, and is maintained by a professional community of dedicated users and data scientists.

What does this course offer you?

This course will introduce you to the fundamentals of neural networks and deep learning. If you take this course, you will not need to take any additional courses or purchase any books on R-based data science.

Companies all around the world use R to filter through the deluge of information at their disposal in this age of big data. You may offer your firm a competitive advantage and further your career by becoming adept in neural networks and deep learning in R!

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