About This Online Course
Continue your learning path in artificial intelligence, machine learning and data science by learning about R programming fundamentals.
This online training course from statistics.com provides an easy-to-understand introduction to programming in R for individuals who have little or no programming experience. R is built to perform statistical processing, and is highly optimized for this one purpose.
Topics covered in the course include understanding file formats and basic R syntax and how to use text editors to write code.
You will learn to read in files, use symbols and assignments and iterate simple loops. We will also cover perform various operations and how to apply common functions to manipulate and analyze data using basic R syntax. The course concludes with a discussion on data structures (including vectors and data frames) and subsetting.
After successfully completing the course, you should be able to install and read data files in R—one of the most popular programming languages in AI and data science.
This online training course utilizes Introduction to Data Technologies, 1st edition (Chapman & Hall, 2009), Murell, P. (available on Amazon). Learners must purchase the book before starting the course.
What You Will Learn
- Install R and RStudio
- Write simple pseudocode and create simple flow charts
- Document code
- Use file management and version control tools
- Perform simple arithmetic and statistical operations in R
- Read data files into R
- Create loops for iteration (e.g., for loop)
- Subset data vectors and lists
- Use apply family of functions for subsetting and basic computations
- Use simple R functions for numerical analysis
- Use simple R functions for basic graphs
- Get familiar with R data structures, especially vectors and data frames
- Perform data manipulation on data frames
- Perform sorting and merging of data frames
Dr. Tal Galili has unbounded enthusiasm for teaching and sharing his expertise in R and statistics. He is a lecturer at Tel Aviv University, Israel, and has taught courses in introduction to computer science with R and various statistics courses. Dr. Galili has received multiple awards for his teaching at the university.
In addition to writing peer-reviewed articles, Dr Galili is an active blogger in the R and statistics communities. He is the founder of R-bloggers, a meta-blog with more than 45,000 subscribers, and writes the blog, R-statistics. Dr. Galili also has published several R packages. He received his Doctorate in Statistics, his Master of Arts in Statistics and his Bachelor of Arts and General Humanities from Tel Aviv University.
Who Should Take This Course
This course is designed for anyone who wants to start studying programming in R—especially those with no prior programming experience.
If you possess some programming experience and want to learn R, you can consider starting first with the statistics.com course, R Programming Introduction Part 2.
A record of completion will be issued, along with professional development credits in the form of continuing education units upon 50-percent completion.
In addition, a Credly badge to add to your LinkedIn profile will be issued upon 80-percent completion of this online training course.
This self-paced, online training course takes place at The Institute for Statistics Education at statistics.com for four weeks. During each session week, you can participate at times of your own choosing—there are no set times for the lessons. Participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.
At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.
$599 (per person)
Register through FedLearn using the special promo code FedLearn22 and receive a five-percent discount on the original online course price.
Continuing Education Unit Credits
This online course provides 5.0 CEUs upon 50-percent completion.
This course is also recommended for 3.0 upper division college credits by the American Council on Education upon 80-percent completion.