- Schedule of Classes - May 30, 2023 7:54PM EDT
- Course Catalog - May 30, 2023 7:15PM EDT
Course information provided by the Courses of Study 2022-2023.
This course builds upon a review of probability and statistics, and basic signal processing principles to explore, develop, and apply algorithms for discovering objects and events in astronomical data, for inference of sophisticated models for populations of objects using frequentist and Bayesian methods, and for visualization and presentation of results to address fundamental questions using persuasive, data-based arguments. Methods include time-series analysis; clustering, classification algorithms, genetic and Markov Chain Monte Carlo algorithms, and neural networks with different architectures. Examples using simulated and actual data will be python based, including Jupyter notebooks.
When Offered Spring.
Prerequisites/Corequisites Prerequisite: background in probability and statistics, lower division math background equivalent for a physics or engineering major, background in statistics at the level of ENGRD 2700 or MATH 1710 or equivalent. Knowledge of Python or MATLAB highly recommended.
Regular Academic Session. Combined with: ASTRO 4523
Credits and Grading Basis
4 Credits Opt NoAud(Letter or S/U grades (no audit))
Class Number & Section Details
- TR Space Sciences Building 622
- Jan 23 - May 9, 2023
Instruction Mode: In Person
Or send this URL: