Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

Accept all cookies Reject all non-essential cookies Find out more

Principles of data visualisation and big data handling, online

Wednesday, 07 May 2025 to Friday, 09 May 2025, 9.30am - 12pm

Apply for this course

This three half-day interactive course will teach you how to effectively visualize and manage large datasets.

You are expected to attend three sessions:

  • Wednesday 7 May, 09:30 - 12:00
  • Thursday 8 May, 09:30 - 12:00
  • Friday 9 May, 09:30 - 12:00

course aim

The course content is divided into (i) Data Visualization principles, (ii) "Large Dataset" Handling, and (iii) practical competencies for data wrangling and visualisation.

  1. Introduction to Data Visualization
  2. Selecting the Right Plots for Data
  3. Understanding Coordinate Systems
  4. Effective Use of Colour Scales
  5. Principles of Figure Design & Telling a Story with Data Visualization
  6. Practical Application of Data Visualization Tools and Software
  7. Big Data challenges and solutions

Note 1: This course adopts a software-agnostic approach. In practical exercises, data wrangling will be performed using Microsoft Excel, a widely accessible and familiar tool for data preparation. For data visualization, we will use a variety of software that has been carefully chosen for its user-friendliness, ensuring that no prerequisite skills are necessary.

Note 2: In this course, 'Big Data' refers to datasets that are too large to be processed manually using basic techniques such as dragging, dropping, or copying and pasting elements or formulas. This includes datasets that can still be handled by consumer hardware but require specialized tools and methods for efficient management and analysis.

course objectives

By the end of this course, participants will be able to:

  • Select appropriate visualizations for different types of data.
  • Apply effective coordinate systems and colour scales.
  • Create visually appealing and informative figures.
  • Communicate their research findings effectively through data visualization.
  • Handle, clean, and transform large datasets for analysis.
  • Use various data visualization tools and software.

participants numbers

30

ATTENDANCE CERTIFICATE ON SURVEY COMPLETION

It is now a requirement that you complete the three short questions in the survey you receive after attending the course. Once you have submitted the survey, you will be sent an email with a link to your attendance certificate. This is to ensure we receive the feedback we need to evaluate and improve our courses. Survey results are downloaded and stored anonymously.

feedback from previous sessions

It was incredibly useful! I wish I had been able to take this course in my first year. Also, the combination of the theory/lecture and the practicals made this course not only interesting, but very helpful! Would 100% recommend.
I found the course to be very insightful, I liked that the practice sessions introduced you to many different tools.
Overall fantastic course. Very useful.

Booking Instructions

Step-by-step guidelines on how to book a Skills Training course.

How to book

Terms & Conditions

These terms and conditions apply to all MSD Skills training courses attendees.

Read the Terms & Conditions

Events from across the University

Leadership in Action – 3-day in person course which runs in June explores what leadership is and looks at some leadership theory. It provides researchers with the opportunity to identify and develop their own leadership style through leading and participating in activities. It also encourages researchers to think about how, through their own developing leadership skills and style, they might enhance research culture. For more information and to apply click here.

Researcher News, Events & Development Opportunities please visit Researchers Hub. 

Research Practice e-learning courses are available to all research staff and students at the University. You can self-enrol at Research Practice Training.

Getting started: beginning your DPhil life in Oxford as you mean to go on – finding a work life balance and looking after your emotions, Getting on: managing professional relationships (supervisors, lab, peers), preparing emotionally for transfer of status, and dealing with DPhil crises along the way, Getting finished – preparing emotionally for submission, your viva, and life after the DPhil. To book visit Workshops and Groups | University Counselling Service

Department of Continuing Education offers Graduate School training programme is for Oxford University postgraduate students. For more details see here.