The hybrid in-person - interactive online course in May 2024 had 99% positive feedback.
Location:
We will deliver this course with two options to participate in the learning. You can choose the attendance option that works best for you:
Wallingford (in-person attendance)
UKCEH Wallingford, Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, Oxfordshire, OX10 8BB.
OR:
Interactive online course using Zoom (joining a live feed - dedicated interactive learning support provided)
Cost:
Students from £449
Professionals from £599
The above prices are for the limited number fo early bird tickets (thereafter £70 more). The in-person places cost £30 more.
Date:
We are deferring the Nov 2024 course to March 2025. We will announce the course details and re-open for sign-up on Tuesday 8 October.
We will start mid-day on Tuesday and finish mid-day on Thursday. There will be an optional software familiarisation session on Thursday 13 March 2 pm (interactive online via MS Teams for all learners)
Please express your interest in the next course here!
Short course description:
This 2-day interactive course will help you understand the benefits of data transformation tools (such as R). The course also includes an optional software familiarisation session on the previous Thursday for those not familiar with the software.
You will learn about aspects such as auditable workflow, repeatability, time-saving, improving efficiency and reduced risk of data loss. You will participate in practical data transformation tool exercises using real environmental datasets to combine and manipulate datasets in different formats from different sources, leading to analysis-ready data. The course also covers cleaning and validation of datasets and best-practice for documentation of scripts and workflows.
We will do many practical exercises. For these, the interactive online learners will be in virtual breakout rooms in pairs or small groups. The facilitators will move from room to room to help you with your exercises.
Learning outcome:
By the end of the course, you will have gained sufficient data transformation skills and knowledge to apply this to your own datasets and projects.
Course objectives:
The course will help you to understand and improve your knowledge and skills on:
- The benefits of data transformation tools
- How data transformation tools (DTT) help users meet quality standards
- How to read in multiple datasets from source in different formats
- How DTTs can be used to clean and validate data.
- How to tidy data and get it 'analysis-ready'.
- Common data transformation operations
- How to combine and integrate datasets from different sources
- Introduction to data management issues and best practice when working with data
Target audience:
Anyone who is looking to work with data in a reproducible manner and currently works mainly in spreadsheets or is looking to prepare data for analysis in R.
e.g. MSc /PhD/ Early career researchers/ Ecologists / Environmental scientists / Environmental consultants
Level:
Beginner – Intermediate (some basic knowledge of R will be an advantage)
We are expecting you to have basic data management skills in MS Excel.
If you are a beginner to R, we strongly recommend that you join a free R familiarisation session on Thursday 7 November 2-5 pm. In that session, we will also support you to ensure you have installed everything correctly.
We will also provide some guidance for semi-structured self-paced learning (an introduction to R Studio and R). You can do this in your own time before the course starts.
Places:
18 places
Hardware and software requirements:
You will need a laptop or desktop computer. A second external screen will be an advantage for those participating online (but is not essential). Having a webcam is desirable (but not essential). If you plan to participate from an open-plan office or noisy environment, please wear headphones with a built-in microphone.
We will use MS Teams to deliver this interactive online course.
We will do lots of practical exercises, so you can continue working on your skills immediately after the training course. You will need to install this software before the course starts.
- R Studio Desktop (free open-source software)
- R programming language (version 4.4 & upwards; free open source software)
We will explain in the joining instructions how to download and install the software.
Accommodation:
For those attending the course in-person, the cost of accommodation is not included in the course fee. Please see our guide to accommodation near UKCEH Wallingford (April 2024)
Course leader:
David Leaver, Environmental data scientist and data steward, UKCEH
David has a background in Chemistry and Atmospheric Sciences and works with scientists, application developers and data managers to improve data management, dissemination and science capabilities in UKCEH. He has developed tools to organise, transform and analyse data from UK-wide pollutant monitoring, ensuring the quality and traceability of results submitted to stakeholders. David has developed and delivered successful courses in relational databases and data transformation in UKCEH over a number of years.
Co-trainer:
Audric Vigier, Information & Data Systems Analyst, UKCEH
Shona Ferguson, Research Associate Environmental Data Scientist, UKCEH
Previous course participants said:
The hybrid delivery of the in-person and interactive online course in May 2024 had 99% positive feedback.
"The course handbook is great and will be a very useful reference tool. The three course trainers were incredibly knowledgeable and worked hard to include everyone and answer questions. David was great, so organised, calm, engaging and included everyone whether in the room or online. Audric and Shona were also fab, very attentive and so on-the-ball! Quickly answering questions and helping out - brilliant teamwork " (Jo Milborrow, Biodiversity Information Service for Powys and Brecon Beacons National Park, May 2024)
"Very clear explanations throughout. Great course organisation. Amazing provision of practical solutions for those asking questions" (learner, May 2024)
"Using 'real' datasets rather than R's training data made the knowledge more applicable and relevant as well as adding to my confidence. I enjoyed the instructor's solutions to learners questions and that we went over these together." (learner, May 2024)
“I enjoyed it all - as a beginner it was good to get the basics and the overview of what's possible. The pace was very good - very calm speaking that I could keep up with.” (Sarah Grinsted, Natural England, May 2023)
“The exercises in the breakout rooms really helped to apply the information from the course and make sure you understood it.” (course participant, May 2023)
“There were lots of opportunities to ask questions and get a good understanding, the environment was good for an online format.” (course participant, May 2023)
“Clear explanations. easy to follow structure. all the instructors were very helpful and approachable. Thank you! “ (course participant, September 2022)
“I liked the fact that there were lots of exercises to do which gave us the chance to apply some of the techniques we'd learnt throughout the course” (course participant, September 2022)