Overview

BIPN 162 Overview

Course Description: Project-based course in which students will use computational notebooks to perform exploratory data analyses and to test hypotheses in large neuroscience datasets, including the differences between unique neuron types, leveraging text mining of the neuroscience literature, and human neuroimaging analyses.

Syllabus & Course Materials

Please see https://github.com/BIPN162/BIPN162_SP24 for the most recent syllabus and course materials.

Course Resources

There is no official textbook for this course. Instead, we’ll be relying on several online resources:

Broadly speaking, the schedule looks like:

Weeks 1-2: Introduction to data science & scientific computing packages

Weeks 3-4: Exploratory data analysis and statistical foundations

Weeks 5-6: Linear models

Weeks 7-8: Dimensionality reduction, classification, and time series models

Week 10: The future of neural data science & final projects.