ΑΙhub.org
Elements of AI – Free online courses for everyone
Elements of AI is a series of free online courses created by Reaktor and the University of Helsinki to encourage as broad a group of people as possible to learn what AI is, what can (and can’t) be done with AI, and how to start creating AI methods. The courses combine theory with practical exercises and can be completed at your own pace.
Courses include:
What is AI?
AI problem solving
Real world AI
Machine learning
Neural networks
Implications
You can take the course for free here.
Sabine Hauert
is Associate Professor at the University of Bristol, and Executive Trustee of AIhub.org
Sabine Hauert
is Associate Professor at the University of Bristol, and Executive Trustee of AIhub.org
AIhub is supported by:
Related posts :
Studying the properties of large language models: an interview with Maxime Meyer
Lucy Smith
11 Mar 2026
What happens when you increase the prompt length in a LLM? In the latest interview in our AAAI Doctoral Consortium series, we sat down with Maxime, a PhD student in Singapore.
What the Moltbook experiment is teaching us about AI
Pursuit, University of Melbourne
10 Mar 2026
An experimental social media platform where only AI bots can post reveals surprising lessons about artificial intelligence behaviour and safety.
The malleable mind: context accumulation drives LLM’s belief drift
Jiayi Geng
09 Mar 2026
LLMs change their "beliefs" over time, depending on the data they are given.
RWDS Big Questions: how do we balance innovation and regulation in the world of AI?
Real World Data Science
06 Mar 2026
The panel explores the tensions, trade-offs and practical realities facing policymakers and data scientists alike.
Studying multiplicity: an interview with Prakhar Ganesh
Lucy Smith
05 Mar 2026
What is multiplicity, and what implications does it have for fairness, privacy and interpretability in real-world systems?
Top AI ethics and policy issues of 2025 and what to expect in 2026
In the latest issue of AI Matters, a publication of ACM SIGAI, Larry Medsker summarised the year in AI ethics and policy, and looked ahead to 2026.
The greatest risk of AI in higher education isn’t cheating – it’s the erosion of learning itself
The Conversation
03 Mar 2026
Will AI hollow out the pipeline of students, researchers and faculty that is the basis of today’s universities?
Forthcoming machine learning and AI seminars: March 2026 edition
Lucy Smith
02 Mar 2026
A list of free-to-attend AI-related seminars that are scheduled to take place between 2 March and 30 April 2026.
