Neuro-insights: Data Science Approaches in Neuroscience Programplan

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This course is recommended for PhD and Master Students that are involved in neuroscience research projects. It is an advantage if the student has knowledge in algebra, linear algebra, statistics, calculus, neurophysiology, and any programming language, especially Python.

It is required that you have a Bachelor degree.

A letter of recommendation from your advisor outlining your project and testifying that you are currently doing neuroscientific research at the Master or PhD level.

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The teaching methodology is oriented by Bloom's taxonomy of educational goals, namely, recollection, understanding, application, analysis, evaluation, and creativity. To promote recollection, understanding, and application, the course will consist of seminars taught by the teaching staff of OsloMet and other guests (experts in neuroscience or data science fields), coding workshops and problem solving oriented projects. Students will actively participate by implementing the full data processing pipeline from extracting the raw data to building visualizations. The pipeline and good habits will be consolidated through repetition in different modules, contexts, and data types, which is known to promote generalization of the knowledge. Organized in pairs, the students will constantly have the opportunity to recollect, explain the content to each other, and justify their work, as well as to provide feedback to their partners. With the intent to prepare the students to go beyond the methods taught in the course, once per module, the participants will read relevant papers in neuroscience, and discuss how to implement their analysis.