Resources

WCM Data Science Google Group

https://groups.google.com/forum/#!forum/wcmdatascience – all MSKCC, Rockefeller, and WCM community members welcome!

R

https://cran.r-project.org/mirrors.html – download R (Check out our getting started with R tutorial)
https://www.rstudio.com/ – download RStudio (R IDE)
https://www.r-bloggers.com/ – collection of R news, tutorials, and resources from many R bloggers
http://tidyverse.org/ – resource page for the tidyverse packages (ggplot2, forcats, haven, readr, stringr, tidyr). Created and maintained by their creator, Hadley Wickham.

Python

https://wiki.python.org/moin/BeginnersGuide/Download – download Python (Check out our getting started with Python tutorial)
https://www.jetbrains.com/pycharm/download/#section=windows – download PyCharm (recommended Python IDE)
https://docs.continuum.io/anaconda/install – download Anaconda, a Python environment manager

Books and interactive tutorials for independent learning

http://r4ds.had.co.nz/ – R for Data Science by Hadley Wickham and Garrett Grolemund (ebook)
https://developers.google.com/edu/python/ – Google class on Python
https://learnpythonthehardway.org/book/ – Learn Python the Hard Way by Zed A. Shaw (ebook), general Python follow-along course
https://www.codecademy.com – interactive online tutorials for a variety of programming languages
http://interactivepython.org/runestone/static/pythonds/index.html – Problem Solving with Algorithms and Data Structures Using Python by Brad Miller and David Runam

Video-based courses for independent learning

https://www.lynda.com/ – free for Weill Cornell students
https://www.coursera.org/ – many courses are free to audit if you don’t want a certificate
https://www.udemy.com/courses/ – courses here may be expensive, but keep an eye out for their $10 sales that happen fairly frequently
https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-046j-introduction-to-algorithms-sma-5503-fall-2005/video-lectures/ – MIT Introduction to Algorithms course

Challenge yourself

https://www.kaggle.com/ – online data science competitions
https://www.drivendata.org/ – more data science competitions
https://www.hackerrank.com/ – general coding practice and competitions

Dataset Resources

https://public.enigma.com/ – a massive collection of datasets collected and curated by Enigma, all available for non-commercial use free to the public

Our Github page

https://github.com/WMCDataSciene