Structured programmes for analysts who need to work at higher levels of rigour, reproducibility, and methodological transparency.
Each track is self-contained and can be taken independently or in sequence.
Core statistical concepts applied to real data, with emphasis on understanding what methods require and what they cannot determine. No prior programming experience assumed.
Practical model construction in health, insurance, or policy contexts. Covers model selection, validation, and the documentation required for internal governance or external review.
Practical implementation of reproducible, version-controlled analytical pipelines using R, Python, Quarto, and Git. Designed for teams producing outputs that must withstand audit or peer review.
Scheduled cohort sessions open to participants from multiple organisations. Announced via this site and direct contact list.
Delivered to a single organisation's team, with syllabus adjusted to the institutional context and data environment.
One-to-one sessions for analysts or researchers with specific methodological questions or ongoing project support needs.
Participants are typically working analysts and researchers in insurance, reinsurance, public health, or regulated bodies who require stronger foundations in statistical practice, more rigorous modelling skills, or the ability to produce reproducible outputs that withstand external scrutiny.
A substantial proportion come from organisations that have identified a gap between the analytical quality they need to produce and the tools and methods currently in use. Others attend to standardise practice across a team or to support a specific project with an elevated evidence requirement.
No prior programming experience is assumed for Track 1. Tracks 2 and 3 assume working familiarity with at least one analytical environment (R, Python, or Stata).
Full syllabi provided upon enquiry. In-house courses include a pre-delivery scoping call to align content with the team's working environment.
To discuss scheduling, in-house delivery, or a coaching arrangement, contact us with a brief description of your team's context and the specific gap you are addressing.