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Lecture notes and slides

Web-hosted lecture notes

The lecture notes for this course are in the process of being published as a standalone, free, online, executable book. The resulting material is intended to be useful to students and educators everywhere, not just students enrolled in this class this term. For that reason, those live in their own, separate website here, with their code in a corresponding Github repository here.

However, these are a work in progress; for many chapters they are kind of just an unorganized pile of plots rather than something coherent. Any chapters that are in that state are labeled with a big warning message at the top.

(In case you’re interested, both websites are created using Jupyter Book.)

Materials from in-class lectures and labs

Unit 00: Introduction; Python basics I

Unit 01: Numeracy and data cleaning; Python Basics II

Unit 02: Descriptive statistics and data visualization

Unit 03: Probability theory

Unit 04: Probability distributions

Unit 05: Linear regression

Unit 06: Hypothesis testing

Unit 07: Timeseries

Unit 08: Spectral analysis

Units 09 and 10: Neural networks and machine learning

Course Information
Schedule
Course Information
Links to datasets