The Agenda

If you’re relatively comfortable with R but find yourself needing to level up your skills this day is for you. Whether you’re hitting in-memory constraints, needing the latest and greatest machine learning algorithm, having to code defensively, or simply needing to get more stuff done, you’ll get a lot from this day of training. This hands-on day will equip you with more tools for performing data engineering and data science in R.

We’ll be covering the following:

• Fast and efficient data processing in R with data.table for improved native R performance
• Working with active external connections in dplyr to push data manipulation to databases
• Leveraging functional programming for working with lists, unstructured data objects, and improving error handling
• Going beyond base R statistics with native-R solutions (caret and the tidyverse) and connected solutions (h2o and spark) for better interfaces, new techniques, and working at scale
• Incorporating Python, JavaScript, and C++ into your R code to extend R or leverage already coded solutions easily

Pre-requisites
You should already be comfortable with R - ideally you’ll have used the tidyverse for data manipulation and data visualisation.
Laptop Required:Yes

• Spec: Machines at or higher than 8Gb RAM + i5 cpu are ideal
• Software: R, R Studio, Java, SQL Server ODBC 13 driver (recommended)
• Subscriptions: Slack for comms & help throughout but will send link closer to the time