Online course: Machine Learning for Bio-Imaging (9–11 March)

[Carlo Pecoraro]

Dear all,

we would like to share an upcoming online training course that may be of interest to members of the MLCSB community: Machine Learning for Bio-Imaging (online, 9-11 March).

This 3-day course provides an introduction to machine learning and deep learning methods for the analysis of biological and biomedical images. The programme combines concise lectures with hands-on Python sessions, focusing on modern, reproducible machine learning workflows for image data.

Key topics include:

• Fundamentals of bioimage analysis and common imaging modalities

• Core machine learning and deep learning concepts for image data

• Convolutional neural networks (CNNs) and U-Net architectures

• Image segmentation and image classification tasks

• Data preparation, augmentation, and handling class imbalance

• Model evaluation and interpretability (e.g. Class Activation Maps)

All practical sessions are based on open-source Python libraries and real biological and biomedical imaging datasets. The course emphasizes methodological understanding and practical implementation, making it relevant for researchers interested in applying machine learning techniques to imaging data within computational biology and biomedical research.

Further details and registration information are available here: https://www.physalia-courses.org/courses-workshops/ml-for-bio-imaging/ 

Best regards,
Carlo

-------------------

Carlo Pecoraro, Ph.D


Physalia-courses DIRECTOR

in...@physalia-courses.org