This hands-on one-day training takes you through the following topics – fundamentals of R, R for ETL, producing reports, and doing data science. Starting with some simple data manipulation, we’ll quickly progress to tools that can make an immediate impact in your day job.
- For ETL, we’ll look at ways to import and export data, transform it, and apply data quality checks along the way.
- For producing reports we’ll see how we can build web reports, PDFs, and interactive dashboards.
- For data science, we’ll look at how R supports you along the process.
By the end of the day, you’ll know some R (including some advanced stuff!) that you can add to your toolbelt.
Take your R code and turn it into reusable packages.
During this hands-on day, we're going to build an example corporate package containing reusable database connections, chart themes, template reports, and utility functions that an organisation might need.
As we work towards our complete package, we'll learn to write functions, build unit tests, write awesome documentation, use source control, and set up continuous integration so that our package will be awesome and trustworthy at the end of the day.
This training day will give you practical knowledge that you can use to support you and other R users in your organisation. You'll replicate code less often and be able to update code in a single location.
There's no point being a data scientist if your work never makes it to production. This hands-on training day takes you through a nifty way to get your code live, scalable, and easily managed. Covering models, dashboards, and other products built in R, plus the Azure Machine Learning Workbench using Python, we'll look at how Docker containers can make managing dependencies a breeze, allow your code to be hosted anywhere, and have it work in high-scale systems.
Spend a hands-on day building some nifty utility apps and bots that will help people inside and outside your organisation get stuff done. Learn how to build bots that can reduce ticket requests and automate processes. Work with Microsoft Cognitive Services to build bots and apps that include powerful features to translate and work with speech provided by users, and process uploaded images. With our working apps, we’ll also be able to peek under the hood at the analytics so we can monitor our apps.
There’s been some changes in R for data science over the past few years. Work hands-on with new packages and ways of doing things to achieve awesome models in many fewer lines of code.
Using packages like dplyr, broom, modelr, recipes, h2o, and furrr we’ll see how we can go from getting data to having an amazing model in no time at all.
This practical day will give people with experience in data science a new set of tools to implement and help them be more productive, whilst for people relatively new to data science it’ll help them get started quickly.