Deep dive in ISI short course for RCS 2026 - Malta
Ahead of RSC 2026 in Malta, the ISI is hosting a series of high-level short courses in collaboration with strategic partners. This curated programme delivers expert-led sessions designed to bridge theoretical rigor with practical application, ensuring participants gain immediate, actionable expertise.
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Today, we speak with Mohamed Yagob, He is one of the speakers leading the upcoming short course, 'Handling High Dimensionality and Infinite Dimensionality'. We sat down with him to discuss the core objectives of the course, the unique value it offers, and the specific skills participants will bring back to their organisations.
What is the main goal of your short course and what will participants be able to apply afterwards?
Mohamed: The main goal of this course is to equip participants with modern tools for analysing high‑dimensional and infinite‑dimensional data, where classical methods such as OLS or MLE break down. In the first part, participants learn how to implement and tune penalized regression methods (Ridge, LASSO and Elastic Net) and Partial Least Squares (PLS) to handle multicollinearity and settings. In the second part, the course introduces Functional Data Analysis, enabling participants to model time‑indexed, spectral, or spatial data using functional PCA and functional regression. Participants will leave able to apply these methods to high dimensional real‑world datasets e.g. in finance, climate, and spectroscopy using R.
Who is this course intended for and what background knowledge is expected?
Mohamed: This course is intended for statisticians, researchers, and data practitioners working with complex, high‑dimensional datasets in academia, central banks, policy institutions, and industry. Participants are expected to have prior knowledge of linear regression and basic likelihood‑based inference. Familiarity with R is required, as the course is hands‑on and focuses on practical implementation rather than introductory syntax. For the Functional Data Analysis component, prior exposure to functional analysis is helpful but not required, as key concepts (such as Hilbert spaces and basis expansions) are introduced during the course. Knowledge on data cleaning would be considered an asset as well.
What makes your course different compared to similar courses in this field?
Mohamed: The course is distinctive in its strong integration of theory, computation, and institutional practice. Delivered jointly by instructors from the University of Malta and the Central Bank of Malta, it explicitly connects high‑dimensional and infinite-dimensional statistical theory with real applied modelling challenges. Rather than treating methods as black boxes, the course emphasises interpretability, model diagnostics, and parameter tuning through cross‑validation. Participants work hands‑on with realistic datasets, compare shrinkage‑based methods with latent‑component approaches such as PLS and PCR, and appreciate the flexibility of functional data analytic approaches over traditional statistical approaches.
What is one key takeaway participants will learn from your course?
Mohamed: A key takeaway is learning how to systematically control model complexity in high‑ and infinite‑dimensional settings. Participants will move beyond ad‑hoc variable selection and gain hands‑on experience with cross‑validation, shrinkage, and component selection strategies that improve model stability and out‑of‑sample performance. They will also learn how re‑expressing data as functions allows classical statistical tools to be extended to continuous domains, enabling flexible modelling of time series, spectral curves, and other functional data structures common in modern applications.
Ready to master your skills in building and evaluating neural network models?
Join David Suda, Monique Borg Inguanez, Fabio Pisano and Mohamed Yagob and step beyond classical methods and explore the cutting edge of modern statistics!
Secure your spot today - Seats are limited!
Date: 2 June 2026
Venue address: Bank Ċentrali ta’ Malta – Central Bank of Malta; Pjazza Kastilja, Valletta VLT 1060, Malta
