skill tracks
Course Overview
Follow the recommended sequence below — each track builds on the previous one. Optional tracks can be done at any time.
Introductory
3 notebooksIntroductory course into the Python programming language. The course is condensed to the minimum requirements for the use of Python in medical data analysis.
DICOM
3 notebooksThis track covers the DICOM file format, conversion to NIfTI and other additional file formats.
Image Analysis
4 notebooksThis track covers exploring, manipulating and measuring biomedical image data.
Data Management
4 notebooksThis track covers working with databases and how to manage and analyze them.
Machine Learning
9 notebooksA series of notebooks designed to build your machine learning knowledge, focusing on fundamental algorithms and techniques using Python with scikit-learn, NumPy, and Matplotlib.
Deep Learning
6 notebooksA series of notebooks to expand your deep learning knowledge. Working with Keras and TensorFlow, you will learn about neural networks, deep learning model workflows, and how to optimize your models.
Prompt Engineering
8 notebooksA set of curated notebooks to help you master prompt engineering for healthcare and beyond. Using real-world medical examples, you will learn how to communicate effectively with language models like ChatGPT, design safe and precise prompts, and apply them in clinical, educational, and research settings.