1 credit
Spring 2026 Laboratory Upper Division
This course introduces students to computational techniques for analyzing real-world neuroscience data using Python and Jupyter Notebooks. Focusing on datasets such as neural time series, students will learn how to preprocess, visualize, and statistically analyze complex data. Topics include basic programming, statistical modeling, and practical applications relevant to neuroscience research. Emphasis is placed on developing hands-on skills for interpreting experimental data and solving real-world problems, preparing students for advanced study or careers in data-driven neuroscience.
Learning Outcomes1Apply Python programming to process and analyze real-life neuroscience datasets, including time-series data.
2Perform statistical modeling and hypothesis testing on neuroscience data to extract meaningful insights.
3Use computational tools to create effective visualizations and interpret their relevance to neuroscience research.
4Design and implement reproducible data analysis workflows using Jupyter Notebooks.
5Combine programming, statistics, and neuroscience concepts to address real-world research questions.
Prerequisites
Restrictions
made by Purdue students.