Summer 2027Oxford + onlineResearch & engineering70% research; 30% engineeringCPD-accredited

Foundation Models

Beyond language. Across domains.

Shared principles across health, science, code, finance and the physical world.

Foundation models are becoming a general approach to learning from the many languages of the world—from clinical records and genomes to code, markets and physical systems. This programme explores the principles they share, how they change across domains, and how to translate and evaluate them in real applications.

Shared foundation-model principles
Depth across major domains
Translation and evaluation in real applications

Shared foundationsPart I · 15%

Representation Learning
Transformers
Emerging Architectures
Tokenisation
Evaluation
Scaling Laws
Multimodality
Transfer

Four domains

Part II

30%

Health, Biology and Scientific Systems

How models learn across clinical, biological and experimental scientific systems.

Topics

Proteins & Proteomics
Imaging, Genomics and Multi-Omics
EHR & Patient Trajectories
Wearables & Biosignals
Chemistry & Materials
Drug Discovery
Autonomous Experimentation

Part III

20%

Financial Markets and Economic Systems

How models learn in adaptive and non-stationary environments.

Topics

Time-Series & Cross-Sectional Data
Multimodal Finance & Economics
Investment, Intelligence & Financial Reasoning
Simulation, Execution & Synthetic Markets
Banking & Credit Systems
Insurance: Underwriting, Pricing & Claims

Part IV

20%

Code, Mathematics and Formal Systems

How models reason within executable and verifiable languages.

Topics

Code Models
Program Synthesis, Repair & Software Generation
Mathematical Reasoning & Formal Problem Solving
Theorem Proving & Verification
RL, Process Supervision & Verifiable Rewards

Part V

15%

Robotics and the Physical World

How models connect perception, prediction and action.

Topics

World Models & Physical Intelligence
Vision-Language-Action and Embodied Foundation Models
Robot Learning, Planning & Control
Simulation, Digital Twins & Synthetic Environments
Industrial Autonomy & Intelligent Systems

Audience & outcomes

Who it's for

Researchers, engineers and technical leaders applying frontier AI across science, technology and industry—with a particular emphasis on cross-domain learning and the transfer of ideas between fields. A working knowledge of machine learning is expected.

What you'll gain

A unified understanding of foundation models across data, domains and systems
Understanding how to translate foundation models into domain-specific systems—and how to evaluate their usefulness, reliability and validity in context
Knowledge of the architectures and scaling principles shaping modern foundation models
Exposure to leading research across health, science, maths, code, finance and robotics
An understanding of how foundation-model methods transfer—and change—across domains
Insight into multimodality, long context, retrieval, memory and world models
A cross-domain perspective for identifying new applications, research directions and product opportunities

Certificate of Participation

Awarded upon completion of the programme.

Certificate of Achievement

Awarded upon successfully passing the assessment on Elandi.ai.

/ OxML 2027 — Oxford

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Foundation Models

Beyond language. Across domains.

Shared principles across health, science, code, finance and the physical world.

Shared foundation-model principles

Depth across major domains

Translation and evaluation in real applications

What you'll gain

A unified understanding of foundation models across data, domains and systems

Understanding how to translate foundation models into domain-specific systems—and how to evaluate their usefulness, reliability and validity in context

Knowledge of the architectures and scaling principles shaping modern foundation models

Exposure to leading research across health, science, maths, code, finance and robotics

An understanding of how foundation-model methods transfer—and change—across domains

Insight into multimodality, long context, retrieval, memory and world models

A cross-domain perspective for identifying new applications, research directions and product opportunities