Available courses

An introductory course covering the fundamentals of formal logic and set theory, including propositions, logical operators, sets, relations, and basic proofs.

A practical foundation for analysing signals as measurements, mathematical models, and data. Participants move from forward and inverse problems to recursive estimation, complementary signal representations, machine-learning baselines, reliable validation, hybrid architectures, and variable-rate repeated signals, with an emphasis on defensible decisions at each step.

An advanced course on signals organised by cycles, phase, and rhythm. It moves from foundational definitions and rhythm functions to cyclic random processes, cycle extraction, rhythm-adaptive estimation, and spectral and time-frequency analysis, ending in a complete data pipeline from fiducial-event detection to phase-resolved statistics and hybrid classifiers.