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AI should be enjoyable
Having fun is the best way to learn . Each of our training sessions is built to be enjoyable, setting your staff up with safe playgrounds to learn how to use AI properly.
Our training is never one-size-fits-all and we will tailor every session by role, organisation, sector, and preferred AI tool.
Our Training
Working with AI
The ideal session if you are looking to begin creating a culture of AI readiness within your team.
We give clear, engaging examples which demystify AI and take it off the pedestal. We will explain how modern AI works, why it isn't clever, and why it is so keen to please.
We will also show clearly how - with adequate adult supervision - AI can lead to immense advantages in the workplace.
The Dos and Don'ts
Want to make sure your team play safe with AI? We will work with your Data Protection Offer to build training which covers exactly which tools to use and which to avoid.
After that, we will get your team going right away with a productive, safe environment to use AI with confidence.
Quality In, Quality Out
Every organisation has their own examples of what good looks like, and this is often the quickest way to get AI producing outputs to your own, precise standards.
In this session, we will help your team score the easiest AI wins possible - by using the resources they already have to quickly make more.
A Prompt Start
Master the art of using AI with the fast-growing discipline of 'prompt engineering'. This way of using AI works just as well for text, image, or even video output, and is quickly becoming one of the most valuable general skills in the workplace.
Every AI practitioner has their own preferred recipe: we'll simply give your team the right ingredients and the confidence to get cooking.
Conscious Unbias
Bias cannot be avoided in AI models, and the best we can do as practitioners is to be aware of it. In this session, we will ask participants to explore their own sources of bias, and how these relate to modern AI tools.
During this workshop, we will work with your team to explain common sources of bias, how to check for it, and how to begin preventing it in their AI work.