R Programming course suitable for everyone, no coding experience or a statistics background needed
What you’ll learn
- Basics of R Programming
- Data Structures in R
- Create your own functions that will enable you to reutilize code.
- Do interesting graph plotting
1.5 total hours
- No Prior Programming Experience Needed.
So, you’ve decided that you want to learn R or you want to get familiar with it, but don’t know where to start? Or are you a data/business analyst or data scientist that wants to have a smooth transition into R programming?
Then, this course was designed just for you!
This course was designed to be your first step into the R programming world! We will delve deeper into the concepts of R objects, understand the R user interface and play around with several datasets. This course contains lectures around the following groups:
1. Basics of R
2. Control Statements in R
3. Functions in R
4. Data Structures in R
5. Plotting Graphs in R
6. Assignments in R
This course was designed to be focused on the practical side of coding in R – instead of teaching you every function and method out there, I’ll show you how you can read questions and examples and get to the answer by yourself, compounding your knowledge on the different R objects.
At the end of the course you should be able to use R to analyze your own datasets. Along the way you will also learn what R vectors, arrays, matrixes and lists are and how you can combine the knowledge of those objects to power up your analysis.
Here are some examples of things you will be able to do after finishing the course:
Do interesting line plots that enable you to draw conclusions from data.
Plot histograms of numerical data.
Create your own functions that will enable you to reutilize code.
Data Structures in R
Join thousands of professionals and students in this R journey and discover the amazing power of this statistical open-source language. This course will be constantly updated based on the student’s feedback.
Who this course is for:
- Business Analysts
- Data Analysts
- Financial Managers
- R learners
- Data Scientists
- Data Engineers
- Entry-level Data Scientists
- Software Engineering Undergraduates
- Graduate Students
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