When you have a to-do list as long as your arm and you just can't get away from your desk, it's hard to really put time aside to learn new things.
With this in mind, the EARL Conference offers 2-day and 1-day passes as well as six half-day workshops on a range of topics. If you can't get more than a day (or even half-day) out of the office, these are for you!
Each workshop is only £115 and you'll walk away inspired with new set of skills:
Writing R Functions for Fun and Profit with Jenny Bryan If there's a bit of R code that you copy and paste repeatedly, package it in a function! User-written functions are a great way to increase your effectiveness in many contexts: scripts, R Markdown documents, R notebooks, Shiny apps, and, of course, R packages. Compared with highly repetitive code, functions can increase code quality, while also reducing programmer aggravation. Many principles of design and process work well across all those domains. This workshop should be useful to those new to writing functions, as well as those more experienced, e.g., ready to start writing packages. We will finish off with some coverage of functional programming and how to use it for iteration in R.
Spark and R with sparklyr One of the frustrations in data science is when the size of a problem crosses from being manageable on a laptop, or a single server, to being too big to fit in memory or too long to process. This often involves switching to a completely different environment and even a different language. Whilst R is a top contender for statistics and machine learning Spark has emerged as the leader for in-memory distributed data analysis.
RStudio's recently released sparklyr package provides tighter integration between R and Spark. In this workshop we will cover data manipulation with Spark as a backend to dplyr and machine learning via MLlib, and explore RStudio's sparklyr package, giving you the power of Spark without having to leave your R session.
Working with the MicrosoftML package MicrosoftML provides a R interface to a set of scalable and distributed learning algorithms and data transformers. The package was initially developed by the research team at Microsoft (MSR), and powers the majority of machine learning applications within Microsoft and within the Azure cloud machine learning ecosystem. In this workshop, you will learn how you can use MicrosoftML’s state-of-the-art machine learning capabilities within R to train high-accuracy machine learning algorithms at blazingly fast speed. We’ll learn the core syntax of the package, how to use it in tandem with your favourite packages for tidy data processing and visualization, and finally how to deploy your trained algorithms in production environments (including Spark clusters). The focus of the workshop will be on Natural Language Processing tasks (NLP), although other use cases will be discussed as well.
Web Scraping and Text Analysis in R Analysing qualitative data can be time-consuming and complex, but can be an invaluable source of insight into patterns and trends in unstructured data. The aims of this workshop are twofold; firstly to introduce participants to web scraping in R using the rvest package, to import data easily and quickly into R. Secondly, this workshop will examine some of the fundamentals of text mining, and show how the tidytext package can be used to simplify this process. Following this session, attendees should be able to perform basic web scraping, be able to transform the scraped data into a useful format, and perform text mining analyses including exploring relationships between words and sentiment analysis, generating compelling visualisations of this data.
Working with GitHub Proper version control is increasingly important to modern Data Science teams, especially when working with Open Source projects. In this workshop, you’ll learn how to get started with version control using Github, the world’s most popular collaboration platform for software development. This introduction will get you started with Github and the version control system that underpins it, git. You’ll learn how to get started working on your own projects as well as how to collaborate with others, and leave the workshop with the information you need to become a confident and productive member of the open source community.
Introduction to Shiny An easy framework for R users to develop web applications, shiny makes it even easier for R users to share the results of their analysis with key stakeholders not familiar with R. In this half day workshop we will introduce those new to Shiny to the key ideas that will help them to build simple web applications. The workshop will emphasise what makes an application suitable for production deployment, ensuring these best practices are adopted from the start. Whilst knowledge of R is expected this workshop is aimed at those with no prior knowledge of shiny. This will be a hands-on workshop with attendees expected to take part in a series of exercises throughout.