Centre for Professional Development and Lifelong Learning

Business and Data Analytics

With skills in business and data analytics being increasingly in-demand in the job market, whether you work in administration, accounting, marketing, or any job that requires you to organize and present any type of data, CPDLL has a suite of courses just for you. Developed and delivered by industry experts, the business and data analytics short courses offered by CPDLL enables you to be able to understand how to analyse data for businesses, assess business situations, support decision making and identify opportunities for creating value.

Business and Data Analytics

Introduction to R for Business

Introduction to R for Business

Overview

R is a powerful free open source statistical computing software that has emerged as the leading programming language for statistics and data analysis.  It is well established in both academia and corporations for robustness, reliability and accuracy, but is still relatively new to the Caribbean region.  R allows the business to combine statistics with computer science in order to extract new insights and new knowledge from the vast amount of data generated from the digital age.  This introductory course in ‘R’ opens to door to the new way of doing business.  Using real cases, allows you  will sit at the computer and learn how to load, merge, clean, reshape, summarize, troubleshoot and transform data into mathematical functions, and produce ‘markdown’ reports using R.   In the final analysis, this course positions you to immediately increase their usefulness to the organisation, as well as to move on to more advanced courses such as Data Science Using R.

Mode of Delivery: Face-to-Face ONLINE

What will I Learn?

On successful completion of the course, delegates will be able to:

  • Load and merge data in R
  • Check for, and handle missing data or errors
  • Transform data using mathematical functions
  • Reshape data into a natural format
  • Use conditional and iterative functions
  • Subset, summarise and aggregate data
  • Produce R Markdown reports
  • Troubleshoot errors or upgrade skills using the internet

Who Should do this Course

Persons who are interested in learning core data science and visualization techniques; persons who are interesting in learning how data science is performed in a business context; those with a specific interest in learning R; professionals tasked with managing data science-oriented projects, and individuals seeking to pursue advanced degrees in Business Analytics and/or Data Science.

Important Information

This course has been offered at a special rate, CLICK HERE to view Terms and Conditions

For our International/ Regional delegates who have successfully completed the requirements of obtaining their Certification, The Centre for Professional Development and Lifelong Learning would be more than happy to deliver your Certificate via a courier service for which you would be required to bear the cost. This sum must be paid to The UWI, Cave Hill Campus prior to dispatch of the certificate. 

For more details, email cpdll@cavehill.uwi.edu and a representative will guide you accordingly.”

At a Glance

  • Registration: Open
  • Date: May 7th – 21st, 2024
  • Time: Tuesday and Thursday, 5pm-8pm
  • Duration: 5 days (15 hours)
  • Certificate Awarded: Certificate of Completion
  • Course Code: PDLL125
  • Capacity: 30
  • Cost: BDS $2,245 (US $1,122.50) BDS $800.00 (US $400.00)

The following topics will be addressed:

  • Working with R and RStudio
  • Importing and understanding data structures in R
  • Installing and loading packages in R
  • How to write clean code with useful comments
  • Using the tidyverse to manipulate data
  • Using for, if and ifelse in R
  • Summarising and aggregating data
  • Subsetting data and creating informative tables
  • Publishing reports and images using R Markdown

No prior knowledge of R is necessary; however, a first-year undergraduate/CAPE/A-level understanding of statistics is strongly recommended.  Specifically, participants should have taken a comprehensive course in statistics covering descriptive statistics.

The course will be delivered through interactive and practical sessions in a computer lab. Online illustrations and videos may be incorporated.

Mr.  Nigel Henry

 

Related Courses

Data Science for Business using R