The project will be to set up a small data analysis pipeline to estimate redshifts using photometry from data extracted from the Rubin DP1 data release. You will be provided with a catalog of Rubin objects that have been cross-matched with reference redshifts from spectroscopic, grism and deep narrow-band photometry. You will use simple machine learning methods from the scikit-learn toolkit to construct a regression algorithm to extract photometric redshifts. Also the way you will extract relevant features from the data, such as filter magnitudes, color, and any other information that might be useful for redshift estimation.