f you’re looking to start a career in data analysis — or just trying to make better business decisions in general — learning the basics of the R programming language is a great place to begin.
About This Workshop
If you’re looking to start a career in data analysis — or just trying to make better business decisions in general — learning the basics of the R programming language is a great place to begin.
By learning the foundations of R, you’ll be able bring your statistical analysis and data visualization skills to the next level.
In this workshop, you’ll get an overview of the R Studio interface, basic R syntax, and best programming practices. You’ll learn how to clean, manipulate, and export data, and use logic, loops, and functions in R.
Takeaways
Learn to import and explore data in R
Gain an understanding of how to program logic, loops, and functions in R
Resources for practicing and building R programming skills
Prereqs & Preparation
Please bring a laptop and be prepared to code along with the instructor. If you're able to install RStudio and R in advance of class, please do so.
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Participants will acquire the skills related to the implementation of unsupervised learning algorithms such as k-means clustering and other analytical methods such as correlation analysis and association rules to derive insights from their data.
By the end of this training, participants will acquire a 360-degree overview of business analytics and R by mastering concepts like data exploration, data visualization, predictive analytics, etc
This R programming course in Singapore forms an ideal package for aspiring data analysts aspiring to build a successful career in analytics/data science.
Today, the word's data is growing at an astonishing rate. It is said that the world's most valuable resource is no longer "oil", but "data". More and more, we see forward-looking corporates harvesting and analysing large complex datasets to improve competitiveness.
This course is for experienced R users who want to apply their existing skills and extend them to the SAS environment. Emphasis is placed on programming and not statistical theory or interpretation.
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