New York University 2 credits Physics
This seven-week lab course provides a detailed introduction to Data Analysis and Python, leveraging tools like ChatGPT to enrich the programming learning experience. Students will use Python toolkits to solidify their grasp of essential concepts, ranging from basic statistical analyses to Fourier analysis. The course blends theoretical lectures with weekly practical coding sessions, fostering a hands-on learning approach. No prior Python experience is needed, making it an ideal gateway to advanced Data Science and Machine Learning topics. The curriculum escalates in complexity, starting with Python basics, probability distributions, resampling, and bootstrap methods. It advances to cover covariance matrices, linear regression, Chi-square minimization, Maximum Likelihood Estimation, and Time-Series analyses, equipping students with a comprehensive understanding of model fitting and predictive analysis. Throughout the course the students create data visualizations and analysis presentations, developing their ability to convey complex data-driven insights. The course culminates in a final project, challenging students to apply their skills to real-world problems. Corequisites: MATH-UH 1020.
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