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Learn how to program in R and use R Studio. The topics include data analytics, data science, statistical analysis, packages, functions, and GGPlot2.

Quick Summary

Learn how to:

Learning how to program in R is a necessary skill for data scientists and data analysts. With this fundamental skill, you'll be able to confidently work with large sets of data and create meaningful visualizations and analyses. The course covers foundational programming concepts in R, including functions, expressions, and variables. Furthermore, you will gain knowledge on how to use the powerful R Studio interface for developing programs and projects. Additionally, topics such as creating vectors in R and understanding various types of variables (integer, double, logical, character) will also be covered. With comprehensive knowledge on all these components of programming in R, you can independently create programs to suit your needs whilst working with data sets efficiently.

Once the foundations are established for programming in R it's possible to build on those skills further by expanding your repertoire of techniques used across basic arithmetic operations, statistical analysis using libraries like dplyr and ggplot2. This will allow people to take that initial knowledge and develop their own projects that enable them to appropriately analyse a set of data from start-to-finish. What’s more fascinating is that even once the syllabus has been completed there appears no shortage on routes available for further learning which leverage the power or R and its unique environment.

Course length:

This comprehensive course provides 10.5 hours of on-demand video, 4 articles, and access to the material on both mobile and TV. Completing the course earns you a certificate of completion as an added bonus. The videos cover all necessary topics when learning about a given subject matter. The articles that accompany the videos offer deeper insight into the lessons covered in them and allow for a better understanding of the material. This certification can be used as proof of knowledge for job qualifications or college courses that require it.

The teaching style and content included in this course are designed to help you gain greater knowledge quickly. With access on both mobile and TV, you can learn at your own pace from any comfortable location – no complex hardware installation required. The material taught in each section of the course is designed to provide a comprehensive understanding by building upon the previous lessons. As an additional incentive, all those who complete this course will receive a certificate of completion which can provide extra credentials when applying for certain jobs or college courses.

Best for:

The R Programming course caters to individuals who are interested in acquiring programming skills in R. This resource is suitable for individuals at all levels of language proficiency, from beginners to advanced users, and offers guidance for enhancing skills with R. This course offers many different types of challenges and assignments, allowing for a comprehensive look at its various aspects and features. Those who are tired of overly complex courses can find solace here, as this course provides a straightforward learning experience designed specifically with beginners in mind.

Students enrolled in the R Programming course will get first-hand experience working on projects that increase their programming knowledge. Furthermore, individuals can utilize these skills to develop their own personalized applications. Those brave enough to take on homework problems will also find themselves rewarded by gaining more comfortable problem solving techniques and strategies outside of the classroom context. Taking this course can lead to success regardless of your initial level of expertise.

About Kirill Eremenko

Kirill Eremenko is a highly experienced Data Science consultant with a background in finance, retail, transport, and other industries. His expertise is derived from his training at Deloitte Australia, where he gained knowledge from esteemed analytics mentors in the field. Now, as an instructor on Udemy, Kirill has shared his knowledge with thousands of aspiring data scientists.

What sets Kirill apart is his ability to combine real-life experience with his academic background in Physics and Mathematics. This unique blend allows him to deliver step-by-step coaching in Data Science that is both professional and easy to understand. Kirill is known for his intuitive explanations, ensuring that even complex topics can be grasped by his students.

Passionate and dedicated, Kirill is committed to making Data Science accessible to everyone. His courses are suitable for beginners and advanced learners alike. By providing practical assignments and real-life analytical challenges, Kirill ensures that his students gain hands-on experience and develop a deep understanding of the core principles of programming and statistical analysis.

Completing Kirill's courses comes with the added benefit of a certificate of completion and lifetime access to the course material. With his guidance, you can acquire the skills needed to excel in the Data Science field and impress potential employers. Benefit from the opportunity to learn from a highly skilled instructor in the industry. Enroll in Kirill Eremenko's courses today and unlock your potential in Data Science.

Inside the R Programming A-Z™: R For Data Science With Real Exercises!

This course offers a thorough, practical approach to learning R programming. By following a series of tutorials and participating in interactive exercises, students can acquire a foundational understanding of coding in R and gain familiarity with the language. With this course, beginners no longer have to struggle with the intimidating concepts associated with a new programming language; instead, they can gradually acquire the necessary skills for solving problems and creating data projects.

The tutorial structure allows students to build their knowledge systematically by starting from basic concepts. After that, they can learn about more advanced topics like data manipulation, data wrangling, computational statistics, and machine learning algorithms. All of these important subjects are presented in an intuitive way that is easy to understand for absolute beginners. Additionally, helpful hints are offered along the way so that even experienced coders can benefit from this course when taking on more challenging task.

This course is structured in a sequential manner. In each new tutorial, we build upon our previous knowledge and take another step forward.

After each video, you acquire a new valuable concept that can be immediately implemented. One benefit is that you learn through real-life examples.

This training includes practical analytical challenges that you will be able to solve. We will solve some of these together, while others will be given as homework exercises.

This course is open to individuals of all skill levels, regardless of their background in programming or statistics. Success can be achieved in this course even without prior knowledge in these fields.

The topics you will cover include:

• Discover the functionalities of R Studio.
• Acquire the fundamental principles of programming.
• This tutorial provides instructions on creating vectors in R.
• Learn about the process of creating variables.
• In R, you can learn about integer, double, logical, character, and other types.
• Learn about the process of creating a while() loop and a for() loop in R.
• Discover the principles and applications of matrices in R programming.
• Gain knowledge in using the matrix() function, as well as rbind() and cbind().
• Discover how to install packages in R.

Frequently Asked Questions

Is R programming easy to learn?

Yes, R is relatively easy to learn for beginners due to its consistent syntax and intuitive functions. However, becoming proficient in the language requires time and practice.

What are the differences between R and Python?

R and Python have both similarities and differences when it comes to syntax and capabilities. R is a language specifically designed for statistical computing and graphics, while Python is a versatile programming language with extensive libraries for data science.

What is R programming used for?

R programming is a powerful language and environment for statistical computing, data analysis, and graphics. It’s widely used in the scientific community to explore and analyze data with the help of various algorithms. It’s also a great tool for creating visualizations to make it easier to understand complex datasets.

What are the different types of data in R?

R supports a variety of data types, such as numeric (integer and double), logical, character, and factor. Additionally, it also offers support for classes and objects defined by the user.

How do I install packages in R?

Packages can be installed from within the R console or through your operating system’s package manager. You can also install packages directly from CRAN, which is the Comprehensive R Archive Network.

What are the benefits of using R for data science?

Using R for data science provides a wide range of advantages, such as robust statistical analysis capabilities, access to powerful packages and libraries, and an open source platform with community support. It also offers excellent data visualization possibilities, which makes it easier to uncover patterns in complex datasets. Additionally, it can be used for modeling and predicting data with machine learning algorithms.