Data Analysis and Visualization in R

You will learn everything from analyzing, manipulating, exploring, illustrating, and reporting data in a far better way than with spreadsheets and other traditional Office products

Features Includes:
  • Self-paced with Life Time Access
  • Certificate on Completion
  • Access on Android and iOS App

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  • Categories

    All Development

  • Duration


  • 65 Students Enrolled

Learn Data Science with R (Data Analysis And Visualization)


What is it?

Data Science for Professionals is simply the best way to gain a in-depth and practical skill set in data science. Through a combination of theory and hands-on practice, course participants will gain a solid grasp of how to manage, manipulate, and visualize data in R - the world's most popular data science language.

Who should take this course?

This course is for professionals who are tired of using spreadsheets for analysis and have a serious interest in learning how to use code to improve the quality and efficiency of their work. At the end of this course, participants will have a developed a solid foundation of the fundamentals of the R language. Participants will have also gained a perspective on the modern data science landscape and how they can use R not only to better analyze data, but also to better manage projects, create interactive presentations, and collaborate with other teams. Whether it's spreadsheets, text documents, or slides, anyone who analyzes, reports, or presents data will benefit from a knowledge of data science programming.

Who should NOT take this course?

While this course covers examples of machine learning in later lectures, this is not a machine learning or a statistics-focused course. The course does go through examples of how to use code to deploy and assess different types of models, including machine learning algorithms, but it does so from a coding perspective and not a statistics perspective. The reason is that the math behind most machine learning algorithms merits a course entirely on its own. There are many courses out there that make dubious claims of easy mastery of machine learning and deep learning algorithms - this is not one of those courses.

A Different kind of data science course

This course is different from most other courses in several ways:

  • We use very large, real-world examples to guide our learning process. This allows us to tie-together the various aspects of data science in a more intuitive, easy-to-retain manner.
  • We encounter and deal-with various challenges and bugs that arise from imperfect data. Most courses use ideal datasets in their examples, but these are not common in the real-world, and solving data-related issues is usually the most difficult and time-consuming part of data science.
  • We are focused on your long-term success. Our downloadable course code is filled with notes and guidance aimed at making the transition from learning-to-applying as smooth as possible.

Who this course is for:

  • Anyone who collects, analyses, reports, or presents data. So pretty much everyone
  • Anyone who is tired of spreadsheets. Again, pretty much everyone
  • Anyone who wants to add a lot of value to their skill set and is willing to invest a few hours per week

Basic knowledge
  • No prior coding knowledge required

What will you learn
  • Students will be able to analyze, manipulate, explore, illustrate, and report data in ways that will set them far apart from those who use spreadsheets and other traditional Office products
Course Curriculum
No of Lectures: 33 Total Duration: 06:31:24
Sandra Webster – May 24, 2021

This course didn't cost much, That is good. It covered a lot of information. It is not for beginners. I have dabbled with R for several years and have coded and done statistics with many other applications. For me, it was a review and mostly a chance to see if I wanted to apply to teach a SimpLiv course. The videos are logically organized. The course packaging leaves a lot to be desired. There is a chat with us tab, but no one ever answers the questions. Likewise, the Q&A is left blank. It does work because I answered another student's question. There are data files and example files that accompany the course. They are buried in the curriculum so that the learner doesn't find them until the last module. It would be better to have them up front so that learners can follow along and do the same activities that they see in the videos. When I finished the course I was planning to go back and practice, but the videos are no longer viewable. For coding and statistics learning even experts need more than one pass. As a statistician, I was disappointed that the data set apparently is not well constructed because the pay variables aren't correlated so that the attrition predictions cannot be good. It is a large set of simulated data but doesn't approximate well to actual data analysis. I am excited to move my R coding into R markdown and Shiny after completing this course. If I decide to move my own online courses to a commercial vendor it will not be Simpliv.

Carlyle Bernard – May 04, 2020

Robert Manley – July 24, 2019

Great course! Very good even for those who already have a data science background but are coming from other tool platforms to R.