Structured multi-session learning experiences with a larger curriculum arc.
Courses are structured learning experiences designed around a coherent curriculum. They usually provide enough time for progressive skill-building, repeated practice, and deeper discussion of research applications.
This four-week online course introduces array-based scientific computing in Python. Participants use NumPy, Matplotlib, and SciPy to analyze and visualize numerical data, work with …
This four-week online course covers the visualization and analysis of spike trains with Python, including their variability and correlations, as well as spike sorting and …
This four-week online course covers preprocessing and visualizing raw EEG and MEG recordings with MNE-Python, statistical analysis of event-related potentials, source separation, …
This four-week online course covers analyzing two-photon and widefield calcium imaging data in Python, from fluorescence extraction, spike inference, ROI selection, automated …
This four-week online course develops practical skills for building scientific Python software that is easier to understand, test, and reuse. Participants organize projects and …
This four-week online course covers the analysis and interpretation of local field potentials with Python, including current source density, filtering, spectral decomposition, …
This four-week online course shows how to turn scientific analyses into explicit, reproducible workflows. Participants will separate code from configuration, track data and …
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