Develop Understanding of R Programming with this edX Course

Shreeyash Kanwade

07 June 2023

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Course Overview

Data Science: R Basics course by edX will introduce you to the basics of R programming for machine learning. You can better retain R when you learn it to solve a specific problem. For example, if you have a real-world dataset about crime in the United States (US), you will need to know the R skills needed to answer essential questions about differences in crime across the different states of the US. This course will provide such concepts of R programming for machine learning.

The curriculum teaches R functions and data types, R syntax, how to operate on vectors, and applications of R programming, like when to use advanced functions like sorting. You will learn how to apply general programming features like "if-else," and "for loop" commands and how to wrangle, analyze and visualize data. On course completion, you will have built a strong foundation that will enable you to pursue in-depth courses later, where we cover concepts like probability, inference, regression, and machine learning.

Rafael Irizarry, the instructor for this online course, is a professor at Harvard University and an excellent teacher who has a very wonderful style of teaching.

"edX curriculum taught me R functions and data types, how to operate on vectors, and when to use advanced functions like sorting."

- Shreeyash Kanwade

Course Structure

It is a self-paced and well-curated beginner-level course spread over 8 weeks. This course is taught online by experienced faculty members. It requires 2 hours per week so as to keep a steady pace with the curriculum.

Technically, this course is divided into 3 prime modules:

Module 1: Basic R syntax
Module 2: Foundational R programming concepts such as data types, vectors arithmetic, and indexing
Module 3: How to perform operations in R, including sorting, data wrangling using dplyr, and making plots

Insider Tips

In order to get the best out of this course, I have included some important tips below that I think you might find useful:

Technical Exhibitionism from the Course

This course will introduce you to the basics of R programming. The curated curriculum covers R's functions and data types, then tackles how to operate on vectors and when to use advanced functions like sorting. You will learn how to apply general programming features like "if-else," and "for loop" commands, and how to wrangle, analyze, and visualize data. Some of the crucial skills you tend to develop upon undergoing this well-curated curriculum include: Computer Programming, Data Manipulation and Exploration, Data Cleaning and Imputation, R Programming, etc.

Prerequisites or References

An up-to-date browser is recommended to enable programming directly in a browser-based interface. Moreover, I would recommend the learner to have a basic understanding of R before pursuing this course to reap maximum benefits. Courses that could be referred for better learning are:

Final Take

This course allowed me to interact with professors like Rafael Irizarry who gave me a lot of guidance for the future. The curated curriculum covered R's functions and data types. We were also given knowledge concerning the operations on vectors and when to use advanced functions like sorting.

Also, the demand for skilled data science practitioners is rapidly growing, and this series prepared me to tackle real-world data analysis challenges.