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External Resources
Helpful links learn more about the foundations of python, signal processing, data science, and other Voytek Lab things.
For python, we recommend using conda as a package and environment manager. We use Jupyter Notebooks a lot, which come packaged with anaconda.
For learning Python, Jake Vanderplas has a lot of great materials, including a Whirl Wind Tour of Python, which is available as sets of Jupyter notebooks.
For improving programming skills, Codecademy's python and git courses are great (and free!).
UCSD course COGS18: Introduction to Python. This course was created by Voytek Lab grad student Tom Donoghue and goes over some fundamentals of Python. The course includes assignments and projects for extra practice.
Digital Signal Processing (DSP) is a large component of analyzing time series data, and a large part of what the lab does. If you want to learn a bit more about DSP, there is a great Interactive Guide and there is also a freely available textbook, DSP for Scientists and Engineers.
For computational modeling of biological neurons, check out this interactive introduction by Jack Terwilliger.
For Data Science, check out the Data Science Handbook, also by Jake Vanderplas. You can also look at the tutorials for Professor Voytek's UC San Diego Data Science in Practice class (COGS 108) (helpfully put together by Voyteklab PhD student, Tom Donoghue). These will step you through the basics, which software to download, how to set up your python and jupyter environments, etc.
It's also helpful to know the basic data science toolkit:
- Anaconda to manage python and packages
- Jupyter notebooks for quick scripting
- Github for version control
- matplotlib + numpy + scipy + pandas + scikit-learn + statsmodels + nltk + BeautifulSoup + bokeh for statistics and data visualization