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The (Delayed) 2019 Training Review

Published: October 13, 2020

tags: r, tidyverse, stan, python, shiny, courses, training, machine-learning

Don’t we all miss 2019 (blame Covid for the long delay in this post). The days of going to work and seeing your work colleagues face to face - and for some of you, attending one of our on-site training courses! 2019 was a great year for us. Not only have we broken new boundaries, we have recruited new full-time staff which have furthermore contributed to the glowing success of the company. The new staff that joined Jumping Rivers in 2019 are as follows -

  • Deborah Washington, Project Operation Manager
  • Anmol Hussain, Finance Officer
  • Dr Rhian Davies, Data Scientist
  • John McIntyre, Data Scientist

You might be wondering, what EXACTLY did 2019 bring for Jumping Rivers. Some interesting data that we have collected regarding the training courses we delivered, can be seen below:

  • Total number of training course attendees was 1192
  • Total number of R training course attendees was 1070
  • Total number of Python training course attendees was 182
  • Total number of Stan / Scala training course attendees was 101
  • Over 100 courses were delivered

To provide a visual representation of how the year went, here are some neat plots I have created using the {ggplot2} R package.

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Average attendees per language

From the graph above, it can be seen that the average number of Python attendees per course was higher than the numv ber of R attendees per course. For courses, we typically cap the class size at around 12 to 15 people. However, we sometimes run larger courses, but there would be multiple trainers onsite. Stan and Scala courses typically have much small class sizes, usually around eight people, this reflects the additional complexity of programming and statistics.

Course length

An interesting observation I have made from the graph above, is that two day courses seem more popular from a Python perspective. Conversely, even though two day courses are popular in R as well, regular 1 day courses seem to be the most prominent approach our clients take when learning R.

R training courses

A very interesting area of my analysis centered around the type of R courses we deliver at Jumping Rivers. We offer courses in three main sectors - analytics, graphics and programming. The bar chart seen above gives us a great indication as to the courses that are most popular with our budding R enthusiasts! We offer introductory and more advanced level programming courses, likewise with our tidyverse courses that include Data Wrangling in the Tidyverse, Functional Programming with {purrr} and Text Mining in R. If you wish to delve deeper into the courses that we offer and want a detailed guide as to what material is covered, go check out our website! You will see that in addition to R and Python, we also offer courses in Stan, Scala and SQL. We have also recently introduced a new version control Git course!

Shall we let the team have their moment - yeah, why not?

A crucial aspect of Jumping Rivers is the team we have here. Each and every person does their job to grow the company and maintain the high standards we have placed on ourselves. Whether it be waking up early to catch a train to deliver a training course, or sitting on our laptops rigorously writing code day after day, we all go the extra mile to meet the needs of our clients and course attendees.

The bar chart below is illustrates the number of courses ran by each presenter in 2019. For the sake of a more accurate depiction, it is worth noting that Rhian and myself (John) joined the company mid to late 2019, respectively

The race was tightly contested in terms of the number of courses taught, with Jamie pipping Theo at the final bend!

Last but not least and in my opinion, the most important of all, is the number of attendees taught. Speaking on behalf of my colleagues and myself, knowing that you have aided the progression of individuals in their understanding of the new, cutting edge programming languages, is hugely rewarding. Jamie wins this one as well so on that note, I pronounce you, Lord Owen (who really hates this post)!


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