We offer the following training courses in addition to the UCL Doctoral Skills Development Programme.
These workshops provide a general overview of how blogs and social media are being used in academia today to network, engage and disseminate research. Workshops will help students begin to build an online profile and presence while their research is still in progress, tap into networks and discussions that relate to their research and develop an understanding of the skills required to make effective use of blogs and social media.
Whether you’re working on a presentation, a website or research materials, nothing tells a complex story faster than an infographic. This intensive course gives you everything you need to create memorable static and interactive infographics. You’ll learn how to find data and tailor it to your audience, as well as how to create maximum impact with your design.
Course content
How to find and analyse data, and match it to the needs of your audience
The importance of good visual storytelling
Designing and presenting graphs and charts to maximise their impact and memorability
The evolution of data visualisation, and examples of best practice
How raw data can be turned into striking visual stories, including both flat graphic design (infographics) and interactives
A mix of lectures and workshops in which participants collaborate and create their own visualisations before presenting them back to the group
The next course runs in Spring 2025 - current DTP and iCASE students can apply via Moodle.
In this highly practical and interactive bespoke course, doctoral students will be gain the knowledge and hands on skills required to set up, launch and run a podcast. After an overview and introduction to podcasting, students will be provided with a template and framework to develop their ideas for the format and content of their own podcast. Working in small groups they will develop plans for a podcast and outline a pilot episode based on that.
The course covers introduction to statistics in the social sciences and health which is taught in pre-recorded lecture format, and a pre-set computer exercise where you will learn to use Stata syntax to interrogate a dataset, undertake management and manipulation of large complex data (such as recode variables, create new variables, and combine several datasets), and conduct simple statistical analyses (t-tests, ANOVA, correlation, chi-square test, and simple linear regression).
The complete L2D course includes:
- Basic Python
- Data Handling
- Supervised Machine Learning
- Unsupervised Machine Learning