Teaching mathematics as capability, not just content.
Undergraduate to doctoral teaching in pure mathematics, AI, data systems and quantitative finance — and new programmes that connect them to careers.
Terminology → Tools → Projects
Students first learn the language of a field, then the tools practitioners use, then prove capability through a project they can show an employer or examiner.
BRAGS
Business Risk Analysis & Growth Strategy — a teaching and research lens that moves students from descriptive and diagnostic analytics to predictive and prescriptive decisions.
New degrees and student showcases
Programme design at CASPAM that connects mathematics with AI, finance and industry.
BS Mathematics with Artificial Intelligence
A curriculum bridge from calculus, linear algebra, probability and optimisation to programming and modern AI — mathematics as the language of intelligence.
Learn more ↗BS Financial Analytics
Mathematics, finance and analytics combined for quantitative careers in markets, risk and financial decision making.
Learn more ↗CASPAM Final Year Project Showcase
Student projects in AI, predictive modelling, business analytics and intelligent systems presented to academic and industry audiences.
Learn more ↗Courses and training offered
Available for degree programmes, faculty development and executive or corporate training.
Artificial Intelligence: Foundations & Knowledge-Based Systems
Understand core AI concepts and implement foundational reasoning/search ideas.
Machine Learning: From Mathematics to Scikit-learn
Build conceptual, computational and project-level ML capability.
Database Systems & Data Modeling
Design relational databases, model data, write SQL and connect data systems to applications.
Business Analytics
Use descriptive, diagnostic, predictive and prescriptive analytics for decisions.
Operations Research & Optimization
Formulate and solve decision models for allocation, planning and optimization.
Portfolio Theory & Risk Management
Connect return, risk, diversification and optimization with quantitative decision making.
Actuarial Mathematics
Develop quantitative foundations for risk, insurance and long-horizon financial decisions.
AI Tools for Teaching, Learning & Research
Use modern AI tools responsibly for learning, teaching, research workflows and project development.
Course modules
Each module ends in a project that becomes portfolio evidence.
| Module | Terminology | Tools | Project |
|---|---|---|---|
| AI Foundations | AI, agent, state, search, heuristic, knowledge, reasoning | Python, Jupyter, search visualizations, simple rule engines | Build a small knowledge-based or search-driven decision system. |
| Python & Data Analytics | data types, dataframe, transformation, aggregation, visualization | Python, NumPy, Pandas, Matplotlib, Jupyter | Create an end-to-end analytical notebook and decision dashboard. |
| Database & ERP Foundations | entity, attribute, relation, PK/FK, schema, transaction, normalization | PostgreSQL, pgAdmin/Neon, SQL, ER modeling | Design and implement a functional module of a university or business ERP. |
| Machine Learning | features, target, train/test, loss, bias, variance, validation, metrics | Python, Scikit-learn, Pandas, NumPy | Build, evaluate and explain a predictive model on a real dataset. |
| Business Analytics | KPI, variance, trend, risk, forecast, scenario, optimization | Excel, Python, SQL, Power BI | Produce a management decision report using the BRAGS lens. |
| Financial Analytics | return, volatility, covariance, diversification, drawdown, risk-adjusted return | Excel, Python, Pandas, optimization libraries | Construct and evaluate a portfolio/risk decision model. |
Current courses
Slides and notes for each course, published through the semester. See the weekly class schedule and the full CASPAM timetable ↗.
Artificial Intelligence
Foundations of AI: intelligent agents, problem formulation, search, knowledge representation, reasoning and knowledge-based systems, with Python implementations.
Open lectures →BS · MSMachine Learning
From the mathematics of learning (linear algebra, probability and optimisation) to building, evaluating and explaining models in Python and scikit-learn.
Open lectures →BS AI · BS Data ScienceDatabase Systems (DBMS)
Relational model, relational algebra, SQL, ER modelling, normalisation and transactions, leading to a working module of a university or business ERP in PostgreSQL.
Open lectures →BS AI · BS Computer Science · BS MathematicsDiscrete Structures
Sets, relations, functions, logic, proof, combinatorics and graphs, extended through systems thinking and system design and modelling towards product modelling.
Open lectures →Courses taught at CASPAM
Since 2008, across BS, MSc, MPhil and PhD programmes.