AI Index Hub - Further Links
AI Training & Awareness
Welcome to the AI Training & Awareness hub. While there is a vast amount of AI content available on the web, this area provides a curated selection of higher-level, organisationally recommended resources. It is designed primarily for Teaching & Learning staff, as well as anyone looking to deepen their understanding of Artificial Intelligence in a higher education context.
Curated Learning Platforms
Explore recommended courses from our trusted partners to build your AI literacy and technical capabilities.
LinkedIn Learning
Access premium AI courses for free through your University of Reading LinkedIn Learning account. Highly recommended for staff:
- Building AI Literacy – Foundational concepts of generative AI.
- Prompt Engineering Masterclass – Techniques for communicating effectively with Large Language Models.
- AI in Education – Exploring the impact of AI on pedagogy and assessment.
Microsoft Learn & Copilot
As our supported everyday AI companion, Microsoft provides excellent training for using Copilot safely and effectively:
- AI for Educators – Learn how to empower your teaching and save time using Microsoft AI.
- Microsoft Copilot Fundamentals – Step-by-step interactive learning paths for everyday tasks.
DEC Courses
Join internal training sessions designed to support your digital capabilities and teaching practices here at the University.
Higher-Level Awareness & Sector Guidance
For staff looking to explore the broader implications, ethics, and strategic use of AI across the higher education sector.
Jisc & Sector Insights
Stay up to date with national guidance on how AI is shaping the future of UK universities.
- Jisc National Centre for AI – Reports, pilots, and insights into AI in tertiary education.
- AI in Tertiary Education – Broad awareness of ethical considerations and digital transformation.
Academic Integrity & Policy
Understand the parameters of using AI tools in your workflow and how to guide students effectively.
- University Guidelines on AI – (Link to CQSD or central policy page).
- Data Privacy & Security – Best practices for keeping institutional data safe when using generative models.