Introduction to Artificial Intelligence in International Education
Instructor
AI for Global Ed Team
Reviews
Course Overview
Introduction to Artificial Intelligence in International Education is a fast-paced, practitioner-focused primer that demystifies generative AI and shows you exactly how to put it to work across the global education landscape.
You’ll move from first principles—how large language models think and the ethics that govern them—to hands-on labs where you experiment with chatbots, copilots and agents tailored to recruitment, mobility, student support and partnership management.
Along the way we unpack real-world case studies, probe data-privacy and bias pitfalls, and give you a ready-to-use action-plan template so you can launch your first AI pilot the moment the course ends. Whether you’re new to artificial intelligence or looking to sharpen your strategic edge, this course equips you with the concepts, tools and confidence to integrate AI responsibly and effectively into international higher-education practice.
What You'll Learn?
- Master AI fundamentals in just 8 hours
- Gain a library of ready‑to‑use prompt templates
- Identify quick‑win automations that save staff time
- Strengthen ethical compliance using the EU AI Act risk framework
- Craft a personalised AI pilot plan for immediate implementation
- Build confidence to lead AI strategy discussions on campus
- International office professionals (recruitment, mobility, partnerships)
- Academic programme leaders with a global remit
- Student services, careers and employability advisors
- Ed‑tech and digital‑learning specialists
- Higher‑education policy makers and quality‑assurance staff
- Curiosity about AI—no coding experience required
- Stable internet connection and modern web browser
- Access to at least one generative‑AI tool (free tier acceptable)
- Willingness to share and discuss workplace examples
- AI Glossary (PDF)
- Prompt Cheat‑Sheet (PDF)
- Personal Action‑Plan template (Word & PDF)
- Case‑Study Workbook
- Five screen‑recorded tool demos
- Recommended reading list and resource links