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\item[The Hyades Star Cluster:] Students receive photometry and parallax measurements from the \emph{Hipparcos} satellite for stars in the Hyades cluster, and must determine the distance, age, and metallicity of the cluster through isochrone fitting. This lab serves as an introduction to the Python programming language, and provides experience in manipulating arrays and making plots. It also illustrates how models and observations can be used together to determine fundamental astrophysical properties.  \end{description}  \textbf{Understanding \item[Understanding  and Reducing CCD Images:} Images:]  Detectors are as important to data quality as telescopes themselves, and students learn about the most common detector in astronomy, the charge coupled device (CCD), by making ``sythetic images" images'' (see Fig.\ \ref{fig:ice})  with an ice cube tray (the CCD) and confetti (the electrons; Fig.\ \ref{fig:ice}). electrons).  Students then move on to manipulating real CCD images obtained at the Campus Observatory, correcting them for common imperfections via bias, dark, and flatfield correction, and then combining images to make aesthetically-pleasing 3-color images of interesting sources.\textbf{Characterizing Transiting Planets:} Students download and analyze data from the \emph{Kepler} satellite, to determine the orbit and radius of an extrasolar planet. This lab introduces the concept of a light curve, applies the concept of CCD photometry, and builds on material presented in lecture on the detection and characterization of extra-solar planets. Data visualization and analysis is carried out in Python, honing students programming and numerical skills.  \item[Characterizing Transiting Planets:] Students download and analyze data from the \emph{Kepler} satellite, to determine the orbit and radius of an exoplanet. This lab introduces the concept of a light curve, applies the concept of CCD photometry, and reinforces the lecture on the detection and characterization of exoplanets. Data visualization and analysis is done in an \ipython\ notebook, which hones the students' programming and numerical skills.