Program Overview

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University Programs

The university offers a wide range of programs, including short and online courses, undergraduate, postgraduate, professional, and research programs.

Subject Areas

• Archaeology and anthropology
• Architectural history
• Business and management
• Data science, computing, maths
• Diplomatic studies and law
• Economics and politics
• Education and study skills
• Environment and sustainability
• History of art
• History, including local and social
• Languages and cultural studies
• Literature, creative writing and film studies
• Medical and health sciences
• Music
• Natural sciences
• Philosophy
• Psychology and counselling
• Religion and theology
• Technology and AI

Course Format

• Day and weekend events
• In-person learning
• Lecture series
• Online learning
• Professional
• Summer schools
• Weekly learning

Undergraduate Programs

Certificates

• Archaeology
• Certificate of Higher Education
• English Literature
• History
• History of Art
• Theological Studies

Diplomas

• Archaeology
• Creative Writing
• English Social and Local History
• History of Art

Advanced Diplomas

• British Archaeology
• IT Systems Analysis and Design (Online)
• Local History (Online)

Pre-Master's

• Advanced Pre-sessional Course for Graduate Students (nine weeks, full-time)
• Foundations of Diplomacy Pre-Master's Course (six months, full-time)

Summer Schools

• Oxford University Summer School for Adults

Postgraduate Programs

Certificates

• Architectural History
• Cognitive Behavioural Therapy
• Ecological Survey Techniques
• Enhanced Cognitive Behavioural Therapy
• Health Research
• Historical Studies
• Nanotechnology
• Patient Safety and Quality Improvement
• Psychodynamic Counselling
• Qualitative Health Research Methods
• Teaching Evidence-Based Health Care

Diplomas

• Cognitive Behavioural Therapy
• Cognitive Behavioural Therapy Severe Mental Health Problems
• Health Research
• International Wildlife Conservation Practice
• Psychodynamic Practice

Master of Studies (MSt)

• Creative Writing
• Diplomatic Studies
• Historical Studies
• History of Design
• Literature and Arts
• Mindfulness-Based Cognitive Therapy
• Practical Ethics
• Psychodynamic Practice

Research Degrees (DPhil)

• Archaeology
• Architectural History
• Cognitive Behavioural Therapy
• English Local History
• Evidence-Based Health Care
• Literature and Arts
• Sustainable Urban Development

Master of Science (MSc)

• Applied Landscape Archaeology
• Cognitive Behavioural Therapy
• English Local History
• Evidence-Based Health Care
• Evidence-Based Health Care Medical Statistics
• Evidence-Based Health Care Systematic Reviews
• Evidence-Based Health Care Teaching and Education
• Experimental and Translational Therapeutics
• Nanotechnology for Medicine and Health Care
• Surgical Science and Practice
• Sustainable Urban Development
• Translational Health Sciences

Professional Programs

Continuing Professional Development

• Business and management
• Cultural heritage
• Data science, computing, maths
• Diplomatic studies
• Education
• Environment and sustainability
• Medical and health sciences
• Nanotechnology and nanomedicine
• Philosophy and ethics
• Psychology and counselling
• Research methods and skills
• Technology and AI
• Urban studies

Research Programs

Research Community

Research at Oxford Lifelong Learning extends across the disciplines and is supported by a research culture that encourages interdisciplinary initiatives.

Research Areas

• Academic staff profiles
• Part-time DPhil programmes
• Research areas
• Research students

Research Forums

• Artificial Intelligence (AI) Steering Group
• Lifelong Learning Pedagogies forum
• Research Ethics Colloquium
• The Vice-Chancellors Colloquium

Course Details: Infectious Disease Modelling

Overview

Infectious disease modelling is a growing field and can provide valuable insights into the spread and control of infectious diseases.

Programme Details

The course begins on January 14, 2026, and consists of 10 weeks of online study with a weekly 1-hour live webinar.

Weekly Schedule

• Week 1: Introduction
  • Installing R and RStudio
  • Using tidyverse
  • Vectors, matrices and data frames
  • Writing functions
• Week 2: Analysing epidemic data
  • Summarising trends
  • Visualising data using ggplot2
  • Estimating the growth rate and reproduction number, R
• Week 3: Epidemic models
  • Building a transmission model
  • The SI model
  • The SIR model
• Week 4: Solving models in R
  • Using deSolve
  • The SI model
  • The SIR model
• Week 5: Stochastic simulations
  • Stochastic vs. deterministic
  • Distribution functions in R
  • Simulating an epidemic
• Week 6: Communicating uncertainty
  • Summarising simulation results
  • Plotting uncertainty
• Week 7: Modelling interventions
  • Vaccination
  • Mass treatment
  • Social distancing
  • Comparing interventions
• Week 8: Individual-based modelling
  • Individual-based SIR model
  • Modelling an epidemic on a square lattice
• Week 9: Fitting to data
  • Fitting methods in R
  • Fitting vs. testing
  • Making predictions
• Week 10: Interfacing science and policy
  • Transparency and reproducibility in science
  • Communicating assumptions and uncertainty
  • Examples from the COVID-19 pandemic

Certification

The course awards 10 CATS points, and students who complete the course will receive a digital Certificate of Completion.

Fees

The course fee is Ł360.00.

Tutor

The course tutor is Dr. Emma Davis, an infectious disease epidemiologist and mathematical modeller.

Course Aims

The course provides a foundation in R programming for infectious disease modelling, with the objective of enabling students to construct and analyse models of infectious disease transmission.

Teaching Methods

The course consists of online study with a weekly 1-hour live webinar, and students are expected to engage in independent study in preparation for the weekly webinars.

Learning Outcomes

By the end of the course, students will be able to use R to solve, simulate, analyse, and visualise basic models of infectious disease transmission, and understand the difference between mean-field and stochastic models.

Assessment Methods

Students will be set two pieces of work, with the first being a 500-word assignment due halfway through the course, and the second being a 1,500-word assignment due at the end of the course. The assessed work is marked pass or fail.

Level and Demands

The course is open to all and is offered at FHEQ Level 4 (i.e., first-year undergraduate level). Students are expected to engage in independent study in preparation for the assignments and the weekly webinar.