Hi everyone Instats is offering a 1-day seminar, Dimensionality Reduction with UMAP and Beyond 2.0, livestreaming on 25 November and led by Dr Nikolay Oskolkov from Lund University and Group Leader (PI) at LIOS. If your work involves high-dimensional genomic, morphometric, or phenotypic datasets, mastering dimensionality-reduction techniques is indispensable for extracting actionable insights and preparing data for downstream analysis. In this intensive workshop, Dr Oskolkov will guide you through both classic linear methods such as PCA and cutting-edge nonlinear approaches including t-SNE and, in particular, UMAP. You will learn why and when to reduce dimensionality, how to code and interpret each technique in R and Python, and how to avoid common pitfalls while maximising interpretability. Real©\world examples¡ªfrom visualizing population structure in genomics to analyzing complex shape data in morphometrics¡ªanchor the theory in hands-on practice, giving you the confidence to preprocess high-dimensional data, select the right algorithms, and communicate your findings effectively. https://instats.org/seminar/dimensionality-reduction-with-umap-and-b Sign up today to secure your spot, and feel free to share this opportunity with colleagues and students who might benefit! Best wishes Michael Zyphur Professor and Director Instats | instats.org Michael Zyphur (to subscribe/unsubscribe the EvolDir send mail to golding@mcmaster.ca)