Teaching

I contribute to teaching and training in data science and genomics in a number of ways — through participation in UCL postgraduate programmes, online courses, and mentoring. My aim is always to make quantitative methods accessible and useful in practice.

Areas

Python for Data Science

Applied data analysis with Python — pandas, NumPy, scikit-learn, and beyond. Focused on practical workflows for researchers working with clinical and genomic data.

Machine Learning

Supervised and unsupervised methods, model validation, and interpretation — with a focus on healthcare and life science applications.

Genomic Data Analysis

Population genetics, sequence analysis, and bioinformatics pipelines. Aimed at life scientists making the transition to computational methods.

Biostatistics

Statistical inference, regression, survival analysis, and study design for clinical and epidemiological research.

UCL ICH — Evidence Based Child Health

I participate in the Evidence Based Child Health module of the UCL Great Ormond Street Institute of Child Health MSc programme, contributing to the training of the next generation of child health researchers.

Online courses

Self-paced courses covering nutrigenomics and data science applied to health — designed for researchers, clinicians, and practitioners who want to understand the genomic basis of personalised nutrition.

Mentoring

I mentor early-career researchers through the in2research programme, which supports students from underrepresented backgrounds in making the transition to postgraduate research.

Get in touch

For teaching or mentoring enquiries, please write to me at drdaviddelorenzo@gmail.com.