University of California, Berkeley 4 credits Astronomy
Undergraduate research is vital to UC Berkeley Astronomy, yet students often lack early computational and professional skills. Astronomy 133 (Research Methods in Astrophysics) bridges this gap through hands-on training in core software (DS9, Astropy, Pandas), advanced statistics (MCMC, Gaussian Processes), and professional workflows (ADS, Overleaf, proposal writing). As the department’s first course to integrate Generative AI into research, Astronomy 133 teaches students to critically and responsibly leverage LLMs alongside statistical rigor and Responsible Conduct in Research (RCR). This inclusive approach empowers a diverse pool of undergraduates to secure and excel in competitive research roles.
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