Instructor: Mark Wilcock

Learning Objectives
This course is a practical hands-on introduction to R for business analysts.  It will help attendees get started with R and use it productively.  It teaches what analysts are most likely to need in their daily work; loading, cleaning, tidying, visualising and transforming data to calculate results and gain insight.
 
Course Structure
This a 2 day workshop.  Both days are full days between 9am and 5pm EST.  The format will be 20% lecture, 20% demo and 60% hands-on exercises.  No previous knowledge of R is required to join the course.  For the sessions, worked example will be provided although students are expected to work through the exercises as much as possible and only view the worked example if they need to.
We'll use lots of examples from wide variety of public datasets. We’ll look at how much people in different countries drink – and how long they live; model Titanic's passengers’ survival; analyse a BBC News article, and then some financial documents; visualise the risk profile of a (fictitious) bank and analyse London property sales.
 
Content
The sessions will last for about 50 minutes with a 10-minute break each hour.  They include
·         get started with R and RStudio (a useful tool for using R)
·         import data from flat files, Excel spreadsheets and databases into R
·         exploratory data analysis – quickly getting familiar with your data
·         visualise data – build line, bar, scatter and other visualisations
·         clean and tidy data
·         transform data to gain insight and calculate results - filter, group, sort and calculate
·         export and save data to CSV, Excel and databases
·         generate reports using RMarkdown
·         use R with Power BI (as a data source, query editor step and custom visual)
·         introduction to text analytics with R
·         introduction to geospatial mapping with R
 
Practicalities
I will provide joining instructions a week or so before the course which will explain how to install R and RStudio (both free).   I will also provide a detailed timetable of the course.  We'll use a variety of free public data sets in all the exercises.  I will make these available a few days before the course.

Delivery Method: Group Internet Based