CUNJC Cambridge
Summer School
AI • Machine Learning • Data Science • Economics • Finance
Join our academic summer school in Cambridge for ambitious students and early-career professionals. It’s an official programme of a University of Cambridge Centre, designed and delivered by award-winning Cambridge academics. Choose from twelve courses across AI, data science, economics and finance. Learn in small groups, work with real data, and build portfolio-ready team projects with close support. Live and learn at Selwyn College, grow your leadership, and get admissions and career guidance, leaving with in-demand skills, strong references and a global network.
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Official programme
A programme of a University of Cambridge Centre, designed and delivered by Cambridge academics with Cambridge teaching standards.
Award-winning faculty
Learn from award-winning Cambridge faculty, combining decades of world-class teaching experience with student-centred innovation.
Cambridge teaching
Experience Cambridge’s famous small-group teaching. Master Python and R through daily interactive labs and immediate expert feedback.
12 academic courses
Choose from 12 specialised courses in AI, Data Science, Economics, and Finance. Tailor your curriculum to your specific career goals.
Team projects
Apply your skills in weekly mentored hackathons. Collaborate in small teams to solve real-world challenges and build a standout portfolio project.
Applied data skills
Master the tools of the future. Learn to wrangle data, build models, and communicate insights using professional Python and R workflows.
Who should apply
Designed for ambitious students (18+) and early-career professionals targeting top graduate schools and data intensive careers.
Cambridge experience
Live the authentic Cambridge student life at Selwyn College. Enjoy en-suite rooms, formal dinners, social events, city tours and punting.
Recognition & outcomes
Gain a certificate of achievement and references. Leave with a portfolio-ready project, admissions insider knowledge, and a global network.Key dates in 2026
31 March
Early-bird application deadline14 June
Final application deadline20–26 July
Online preparation course1–16 August
Academic Session One16–30 August
Academic Session TwoOur teaching is recognised by global awards and nominations
Four pillars of the CUNJC Cambridge Summer School
Academic programme
‣ Learn from award-winning faculty‣ Cambridge teaching style & standards
‣ Pick from 12 courses on AI, ML, Econ
‣ Learn core idea & tool demo in lecture
‣ Practise tools on real data in class
‣ Achievement certificate & references
‣ Deeper understanding & retention
‣ Daily progress with live coaching
‣ Mastery of analytical methods
‣ Independent problem-solving
Hackathon projects
‣ Work in small teams + mentor‣ Apply classroom tools to real problem
‣ Analyse real-world data in Python/R
‣ Build shareable output
‣ Present findings at the showcase
‣ Hands-on coding/data experience
‣ Teamwork and project skills
‣ Confidence using applied data tools
‣ A portfolio-ready finished project
‣ Feedback from expert instructors
Professional development
‣ Keynotes by renowned academics‣ Career panels with top executives
‣ Leadership coaching sessions
‣ Cambridge-led admission workshops
‣ Networking events with speakers
‣ Actionable career goals
‣ Insider admissions know-how
‣ Practical leadership toolkit
‣ References & recommendations
‣ Professional & academic network
Social programme
‣ Experience Cambridge student life‣ Live & learn at Selwyn College
‣ Attend formal hall dinners
‣ Join guided city tours & punting
‣ Take a memorable trip to London
‣ Strong sense of belonging
‣ Deeper cultural fluency
‣ Lasting friendships worldwide
‣ International mentor network
‣ Unforgettable Cambridge memories
Academic programme courses
Academic programme courses
We run two sessions in Cambridge: Session One, 1–16 August, and Session Two, 16–30 August. In each session we offer all 12 of our courses. You can join us for one or both sessions, choosing one course per session. Every course runs for two weeks and combines lectures, small-group classes and team projects. Data Science & AI
Mathematical methods
Calculus, linear algebra, and optimisation as modelling tools in economics and data science.
Calculus, linear algebra, and optimisation as modelling tools in economics and data science.
Statistical methods
Probability and statistics for empirical analysis, including estimation and hypothesis testing.
Probability and statistics for empirical analysis, including estimation and hypothesis testing.
Causal data science
RCTs, IVs, DiD and quasi-experiments for causal inference and treatment effects estimation.
RCTs, IVs, DiD and quasi-experiments for causal inference and treatment effects estimation.
Econometrics
Regression analysis and maximum likelihood to estimate statistical models and test theories.
Regression analysis and maximum likelihood to estimate statistical models and test theories.
Machine learning
Supervised and unsupervised learning to train and evaluate prediction & classification models.
Supervised and unsupervised learning to train and evaluate prediction & classification models.
Artificial intelligence
Reasoning, natural language processing, and reinforcement learning for intelligent systems.
Reasoning, natural language processing, and reinforcement learning for intelligent systems.
Economics & Finance
Microeconomics
Game theory, decision-making and information to analyse strategies and incentives.
Game theory, decision-making and information to analyse strategies and incentives.
Macroeconomics
Growth, business cycles, and policy to study how economies evolve and are managed.
Growth, business cycles, and policy to study how economies evolve and are managed.
Network economics
Network structure and diffusion processes to model systemic connections and spillovers.
Network structure and diffusion processes to model systemic connections and spillovers.
Complexity economics
Equilibrium, emergence, and agent-based models to understand systemic risk and crises.
Equilibrium, emergence, and agent-based models to understand systemic risk and crises.
Quantitative finance
Time-series modelling and derivatives pricing to analyse and forecast financial market behaviour.
Time-series modelling and derivatives pricing to analyse and forecast financial market behaviour.
Financial markets
Asset pricing theory and behavioural biases to understand what drives risk/returns & bubbles.
Asset pricing theory and behavioural biases to understand what drives risk/returns & bubbles.
Programme brochure
Download the full brochure to discover how our summer school can transform your academic and career trajectory.
