The students acquire the following skills during the course of the semester:
• Basics of personal conduct in a laboratory setting, with an emphasis on safety.
• Setup, calibration, troubleshooting, and operation of electronic, digital, optical and mechanical equipment, such as oscilloscopes, power supplies, photo-detectors, lasers, microscopes, and pendulums.
• Use of modern computational techniques and programming languages for efficient and scalable data acquisition, storage, and analysis practices, through the use of Python programming language and relevant free and open-source scientific packages.
• Mastery of relevant mathematical concepts, such as Poisson/Normal distributions, Chi2 fitting, Discrete Fourier transforms, random walk, and nonlinear/chaotic systems.
• Quantification and reporting of systematic and statistical uncertainties (as appropriate) in the experimental measurements.
• Presentation of acquired results in scientific writing, as well as to an audience in a scientific setting.