Part I
Foundations
How foundation models learn across sequences, signals, graphs and physical systems.
Topics
- Representation learning
- transformers
- emerging architectures
- scaling laws
- multimodality and transfer
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Beyond language — across health, biology, code, financial markets and the physical world.
Foundation models are expanding beyond natural language. Across healthcare, biology, software, music, finance and the physical world, valuable information is expressed through clinical events, physiological signals, genomic sequences, molecular structures, source code, mathematical expressions, acoustic patterns, market data and physical trajectories.
This programme explores how foundation-model principles change across these different data languages.
Hover a domain to explore.
Research
70%
Advancing the science of foundation models across domains
Product & Engineering
30%
Engineering and applications in real-world systems
Season
Summer 2027
Format
Hybrid
Certificate of Participation
Awarded to every participant.
Skills accreditation
Verified certificate, subject to passing the exam.
Who it's for
Researchers, engineers, scientists and technical leaders across health, biology, chemistry, software, finance, audio, robotics and the physical sciences. Participants should have a working understanding of machine learning.
What you'll gain
A unified journey
From shared scientific foundations to the frontiers of domain-specific intelligence.
Curriculum structure
Six connected parts, from foundations to the physical world.
Programme focus
70% research · 30% engineering and applications.
How foundation models learn across sequences, signals, graphs and physical systems.
Topics
How models learn across clinical, biological and experimental scientific systems.
Topics
How models learn in adaptive and non-stationary environments.
Topics
How models reason within executable and verifiable languages.
Topics
How models learn from sound, structure and composition over time.
Topics
How models connect perception, prediction and action.
Topics
Natural language is only one of the many languages through which the world can be understood.
/ OxML 2027 — Oxford
Leave your email and we’ll write when applications open for the three 2027 modules.