Physics Data Analysis Course
This course equips you to handle authentic physics data by cleaning time-series, fitting damped oscillators, estimating uncertainties, and evaluating models using strong statistical methods. Develop publication-ready analyses with contemporary Python scientific tools and comprehensive diagnostics, ensuring reliable and reproducible results in physics research.
from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Gain expertise in precise data analysis through this practical course. You will model damped oscillations, use signal processing and filtering techniques, and manage noisy time-series data effectively. Practice nonlinear fitting, uncertainty assessment, model evaluation, and thorough residual checks while creating reproducible processes, professional visuals, and detailed reports suitable for publication or scrutiny.
Elevify advantages
Develop skills
- Time-series preparation: efficiently clean, resample, and remove trends from noisy physics data.
- Signal analysis: utilise FFT, filters, and wavelets to derive key physical properties.
- Nonlinear model fitting: perform least squares and resilient fits for oscillation models.
- Error quantification: apply bootstrap, covariance matrices, and Bayesian methods for uncertainty.
- Fit evaluation: analyse residuals, assess models, and produce superior fitting reports.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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