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    "# Resources for further learning\n",
    "\n",
    "The [website for this workshop](http://people.duke.edu/~ccc14/cfar-data-2016/index.html) is awesome :-)\n",
    "\n",
    "General coverage of data science tools useful for biologists are covered very well in these two biologist-friendly books:\n",
    "\n",
    "- [Practical Programming for Biologists](https://www.amazon.com/Practical-Computing-Biologists-Steven-Haddock/dp/0878933913)\n",
    "- Computing Skills for Biologists – A Toolbox (to be published by Princeton Press - not available yet)\n",
    "\n",
    "The next section is for those of you who want to learn to program in Python. The first link provides a *learn by doing* book for coding in Python (a philosophy I recommend), the second link is a more advanced coverage of using Python for data science, and the third provides a comprehensive guide to Python learning resources, and the thrid is a a more \n",
    "\n",
    "- [Learn Python the Hard Way](https://learnpythonthehardway.org/book/)\n",
    "- [Python Data Science Handbook](https://www.amazon.com/Python-Data-Science-Handbook-Essential/dp/1491912057)\n",
    "- [Links to Learning Resources at the The Hitchhiker’s Guide to Python](http://docs.python-guide.org/en/latest/intro/learning/)\n",
    "\n",
    "The best resource for Pandas is probaly the [website](http://pandas.pydata.org)\n",
    "\n",
    "If you want to learn R and some statistics, my favorite book for beginners is:\n",
    "\n",
    "- [R in Action (2nd edition)](https://www.manning.com/books/r-in-action-second-edition)\n",
    "\n",
    "And to learn how to write modern idiomatic R, \n",
    "\n",
    "- [R for Data Science](http://r4ds.had.co.nz)\n",
    "\n",
    "If you get stuck, you can ask programming questions at [StackOverflow](http://stackoverflow.com)\n",
    "\n",
    "Finally, links to the various Python packages that we use for data analysis and visualizaiotn in this workshop:\n",
    "\n",
    "- [Python](https://www.python.org)\n",
    "- [Jupyter](http://jupyter.org)\n",
    "- [Pandas](http://pandas.pydata.org)\n",
    "- [Matplotlib](http://matplotlib.org)\n",
    "- [Seaborn](https://stanford.edu/~mwaskom/software/seaborn/)\n",
    "\n"
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