Online courses

Online learning

In addition to the workshops we deliver to groups in the classroom, we offer online training courses for researchers so that individuals can learn and complete courses at their own pace. We have our own online training platform that students can engage with directly, alternatively we can provide the content so that you can integrate it directly into your own virtual learning environment.

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Advantages of online training

  • Individuals can learn at their own pace and in their own time
  • Suitable for part-time and distance learners
  • Cost effective solution for large numbers of students
  • Can be combined with face to face workshops

We are currently expanding the range of courses that we offer online, we also design online content for clients directly so please do get in touch if you have a specific project in mind.


Our online courses include


Electv Brochure 2018-19

cropped-electvlogo.png Intellectual property essentials: copyright, teaching & commercialisation

Intellectual property (IP) is considered to be a “creation of the mind” and a considerable amount of IP is created in universities. It is now essential for researchers to equip themselves with an elementary knowledge of the subject because IP is relevant to scholarly publishing, teaching materials, patents and much more.

  • An introduction to the various types of intellectual property and how these apply to scholarly pursuits
  • Can be completed in one day or at the individual’s own pace over a longer period of time
  • Consists of case studies, videos, multiple choice quizzes and further resources

Electv Brochure 2018-19



cropped-electvlogo.png Introduction to R statistical software & data visualisation

(coming soon – spring/ summer 2020)

A series of four introductory courses to the freely available R statistics software, now the most commonly used software for statistics in academia. An essential skill for researchers in quantitative subjects.

R101: An introduction to R

  • Data & questions
  • Descriptive statistics
  • Numerical summaries
  • Graphical displays
  • Exploration vs confirmation

R102: Graphs & visualisation

  • Exploration of a real dataset
  • Basic graphs using the package ggplot2
  • Bar plots, scatter plots, histograms, box plots, density plots
  • Plot data on maps
  • Motion charts

R103: Inferential statistics & statistical modelling

  • Variables, probability, the Normal distribution
  • Statistical tests and hypothesis testing
  • Confidence intervals
  • Student’s t-test, chi-squared test

R104: An introduction to R programming

  • Variables and data types
  • Functions
  • Conditions, loops
  • R programming
  • Writing your own package



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