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Pre-requisites

Data Carpentry's teaching is hands-on, so participants need to bring their own laptops to insure the proper setup of tools for an efficient workflow. In exchange, you will leave with a working version of R, and the skills to use it.

These lessons assume no prior knowledge of the skills or tools, but working through this lesson requires working copies of the software described below. To most effectively use these materials, please make sure to install everything before working through this lesson.

Please note all of the requirements specified below are free. Get in contact if you are about to hand over any money for this course because you shouldn't be.

Pre-course Objectives

  • Install R
  • Install R studio
  • Sign up for a Google docs account
  • Download and install a speadsheet programme
  • Join Slack

Steps

1. Charge your laptop

We'll provide a power bar, but it will be easier if you have a fully charged laptop. There are two lessons in each evening session, lasting around 45 minutes each so 2 hours of 'juice' should be enough.

2. Install R and R studio

We're going to get you up and running in R which is a highly respected, free statistics package used by academics around the world. We will also install a friendly interface to R called RStudio.

  1. Download and install R from here

  2. Download and install RStudio. This is a nice shiny interface for R, and the easiest way to use it. Download it here. There should be an 'installer' for your operating system.

{% include rSetup.html %}

3. Sign-up for a Google docs account.

We'll be using Googlesheets for two reasons. Firstly, they allow online collaborative editing. Secondly, starting your data 'pipeline' in the cloud will allow you to produce 'realtime' analytics.

Sign-up for an account at here.

4. Download and install a Spreadsheet program

Only, if you don't already have Excel or similar already installed.

{% include spreadsheetSetup.html %}

5. Join our group on Slack

Slack is a geeky version of WhatsApp, but much better for coding and collaborating. We will use it to share files. You can use it chat, to ask questions, and later to become part of the Datascience Breakfast Club.

See you there!