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 General relativity is the fundamental theory for gravitational waves. But since this is a programming/data analysis oriented project, it's fine to focus more on the programming side rather than the theory side. Nevertheless, we'll try to hold some tutorial sessions to grasp some basic knowledge of general relativity.
 
 A note that I found useful when I learned general relativity is [this](https://arxiv.org/pdf/gr-qc/9712019.pdf). There is a series of online course recording from Susskind in [here](https://www.youtube.com/watch?v=JRZgW1YjCKk&t=1106s).
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+Nevertheless, for this project, there is no harm for us to just deal with gravitational waves as some signals, just similar to some sound signals.
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+## Data Analysis of Gravitational Waves
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+We'll use [Pycbc](www.pycbc.org) a lot, which is the primary software that we used and developed for gravitational wave data analysis. 
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+A very useful tutorial can be found [here](https://github.com/gwastro/PyCBC-Tutorials). I strongly recommend you to go over the tutorial 1-4 in this repository.
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+[LIGO open data workshop](https://www.gw-openscience.org/static/workshop4/) is also a good place to learn!
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+Note that at the core of gravitational wave data analysis is the match filtering technique, in which the gravitational waveform templates play a major role. So it's very important to learn how to generate a template for gravitational-wave signal. This can be found [here](http://pycbc.org/pycbc/latest/html/waveform.html).
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+## Machine Learning
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