ASTR 596

Spring 2023

Part of Term 1
Jan 17-May 3
Seminar in Special Topics
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Credit: 0 TO 16 hours.

Approved for both letter and S/U grading. May be repeated. Prerequisite: Consent of instructor.

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CRN Type Section Time Day Location Instructor Section Details
48224
Lecture
FDS
2:00PM -3:20PM
MW
Astronomy Building
Narayan, G
Part of Term:
1
Date Range:
01/17/23-05/03/23
Credit:
4 hours
Section Title:
Fundamentals of Data Science
Section Info:
This course will cover a number of statistical techniques that are relevant to astrophysical studies. These include robust statistics, regression, model building and hypotheses testing, MCMC methods, parameter estimation, time series analysis, clustering and dimensionality reduction, supervised machine learning, and hierarchical modeling. These techniques are used in almost every paper you'll read. The goal of this course is to ensure you understand how these techniques work, and what their implicit assumptions are, so that you can make informed modeling choices with real data. You'll also learn how to use the tools that implement these techniques, best practices for writing code and version control, and how to craft detailed analyses into a readable telescope or grant proposal.
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