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Digital Skills for Researchers

Course Purpose and Introduction

Science has a
replication/reproducibility issue

Many fields

  • Economics
  • Psychology
  • Biology

We have the technology

Computation has becoming an increasingly large part of the scientific process
Data collection and storage, processing, analyses, visualization and conclusion all depend more and more on computation

Course Aims

By the end of this course you should have the knowledge
and skills to publish reproducible science research.

(and some of you may actually publish!)

Course Philosophy

You will be assessed on personal progress,
not assessed relative to your peers.

Skills are means to an ends, not the goal.

Course Structure

  • 9 modules
  • Fist half of the course is technical skills
  • Second half is more conceptual, using skills learnt in the first half
  • Ongoing assignments and work on your project

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Science has a replication/reproducibility issue
Many studies across many fields reporting low success rates for replication
<50%

Our research should be reproducible

This can feel daunting. Making our work visible to everyone else sounds like a scary proposition.

The Structure of the course

11 Modules covering project management, data management, computing, visualization, sharing, licensing and publishing. Learn how to integrate these skills together into a scientific work flow. During the course you will apply what you are learning to your project, working so that is (100%) reproducible science. The focus of this course is as much on creating reproducible workflows as it is the individual tools and skills that go into creating those worlflows.