Running the course on the cloud: Instructions

Information for running the course using open source cloud based technologies

For this course we will be using github to share and publish course material and class projects. All participants are required to setup a github account and provide their username at least one week before the first session. Participants who fail to do so will not be able to follow the course.

You will also be provided with your individual (cloud) server with all the course material automatically uploaded from the (raw files) course website github repository and directly linked to your individual github repository. All necessary software, data, and course material will be automatically uploaded on your personal servers before the course begins.

You should log in your personal (cloud) server at least 2 days before the first session, following these instructions. You can also see the real time cost for your server during the course at any time. You should update your server's content before every session with the latest course content by following these instructions.

Useful Technical Resources

We will be using a number of tools in this course: GitHub, R, knitr, Slidify, to name a few. You can find here some useful technical resources as starting points. Moreover, these are some more instructions you may find useful.

Class Group Project and the Sample Data Analytics Projects Page

For the class group project, every group (sizes of 3-5 people per group) is required to develop a data analytics case for which data is also gathered and, when possible, shared. The project deliverable will be a case study structured like the examples in the Data Analytics Projects page.

Replicability and Reuse: A key goal of the course is to learn how to develop replicable and reusable data analytics processes and tools. As part of the class group project requirement, every group will replicate and reuse the project of another group. For this purpose, groups are required to provide instructions for replicability and reuse of their case, as outlined for the examples in Sample Data Analytics Projects page.