Linear algebra tutorials from Khan Academy available at https://www.khanacademy.org/math/linear-algebra (retrieved January 2016)
Probability and statistics tutorials from Khan Academy at https://www.khanacademy.org/math/probability (retrieved January 2016)
Coursera course on linear algebra, which uses Python, available at https://www.coursera.org/course/matrix (retrieved January 2016)
Introduction to probability by Harvard University, available at https://itunes.apple.com/us/course/statistics-110-probability/id502492375 (retrieved January 2016)
The statistics wikibook at https://en.wikibooks.org/wiki/Statistics (retrieved January 2016)
Electronic Statistics Textbook. Tulsa, OK: StatSoft. WEB: http://www.statsoft.com/textbook/ (retrieved January 2016)
Statistics for hackers by Jake van der Plas, available at https://speakerdeck.com/jakevdp/statistics-for-hackers (retrieved January 2016)
Explore Data: Data Science + Visualization by Roelof Pieters, available at http://www.slideshare.net/roelofp/explore-data-data-science-visualization (retrieved January 2016)
High Performance Python (1.5hr) Tutorial at EuroSciPy 2014 by Ian Ozsvald, available at https://speakerdeck.com/ianozsvald/high-performance-python-1-dot-5hr-tutorial-at-euroscipy-2014 (retrieved January 2016)
Mastering Linked Data by Valerio Maggio, available at https://speakerdeck.com/valeriomaggio/mastering-linked-data-with-ptyhon-at-pydata-berlin-2014 (retrieved January 2016)
Fast Data Analytics with Spark and Python by Benjamin Bengfort, available at http://www.slideshare.net/BenjaminBengfort/fast-data-analytics-with-spark-and-python (retrieved January 2016)
Social network analysis with Python by Benjamin Bengfort, available at http://www.slideshare.net/BenjaminBengfort/social-network-analysis-with-python (retrieved January 2016)
SciPy 2015 conference list of talks, available at https://www.youtube.com/playlist?list=PLYx7XA2nY5Gcpabmu61kKcToLz0FapmHu (retrieved January 2016)
Statistical inference in Python, available at https://sites.google.com/site/pyinference/home/scipy-2015 (retrieved January 2016)
Ibis: Scaling Python Analytics on Hadoop and Impala by Wes McKinney, available at http://www.slideshare.net/wesm/ibis-scaling-python-analytics-on-hadoop-and-impala (retrieved January 2016)
PyData: The Next Generation by Wes McKinney, available at http://www.slideshare.net/wesm/pydata-the-next-generation (retrieved January 2016)
Python as the Zen of Data Science by Travis Oliphant, available at http://www.slideshare.net/teoliphant/python-as-the-zen-of-data-science (retrieved January 2016)
PyData Texas 2015 Keynote by Peter Wang, available at http://www.slideshare.net/misterwang/pydata-texas-2015-keynote (retrieved January 2016)
What's new in scikit-learn 0.17 by Andreas Mueller, available at http://www.slideshare.net/AndreasMueller7/whats-new-in-scikitlearn-017 (retrieved January 2016)
Tree models with Scikit-learn: Great models with little assumptions by Gilles Loupe, available at http://www.slideshare.net/glouppe/slides-46767187 (retrieved January 2016)
Mining Social Web APIs with IPython Notebook (Data Day Texas 2015) by Matthew Russell, available at http://www.slideshare.net/ptwobrussell/mining-social-web-ap-iswithipythonnotebookddtx2015 (retrieved January 2016)
Docker for data science by Calvin Giles, available at http://www.slideshare.net/CalvinGiles/docker-for-data-science (retrieved January 2016)
10 more lessons learned from building Machine Learning systems by Xavier Amatriain, available at http://www.slideshare.net/xamat/10-more-lessons-learned-from-building-machine-learning-systems (retrieved January 2016)
IPython & Project Jupyter: A language-independent architecture for open computing and data science by Fernando Perez, available at https://speakerdeck.com/fperez/ipython-and-project-jupyter-a-language-independent-architecture-for-open-computing-and-data-science (retrieved January 2016)
Scikit-learn for easy machine learning: the vision, the tool, and the project by Gael Varoquaux, available at http://www.slideshare.net/GaelVaroquaux/slides-48793181 (retrieved January 2016)
Big Data, Predictive Modeling and tools by Olivier Grisel, available at https://speakerdeck.com/ogrisel/big-data-predictive-modeling-and-tools (retrieved January 2016)
Data Science Python Ecosystem by Christine Doig, available at https://speakerdeck.com/chdoig/data-science-python-ecosystem (retrieved January 2016)
New Trends in Storing Large Data Silos in Python by Francesc Alted, available at https://speakerdeck.com/francescalted/new-trends-in-storing-large-data-silos-in-python (retrieved January 2016)
Distributed Computing on your Cluster with Anaconda - Webinar 2015 by Continuum Analytics, available at http://www.slideshare.net/continuumio/distributed-computing-on-your-cluster-with-anaconda-webinar-2015 (retrieved January 2016)