Tools and Tutorials
Whether you came here with your own data or discovered a dataset among our data resources, this curated list of tools and tutorials can help you make the most of your data. A subset of useful information about each resource is included on this page, but more information (including links how to gain access to it) can be found by clicking on the resource's name.
|Data Science Services Workshop: Screen Scraping: A Hands-on Introduction||Tutorial||
Tutorial for scraping websites in Python. Part of a Data Science Services workshop series by Harvard’s Institute for Quantitative Social Science.
|DiRT: Digital Research Tools||List||
A list of digital research tools categorized by research activity/purpose, including content management, data visualization, network analysis, statistical analysis, and more
|R, Python, MATLAB|
R library for visualization and plotting
|Github Markdown Tutorial||Tutorial||
Introduction to markdown
Tutorials and code for implementing various machine learning techniques using H2O.ai
A list of various tutorials on implementing machine learning techniques using H2O.ai
|Interactive data for the web - Bokeh for web developers||Tutorial||
Tutorial for using Bokeh, a Python visualization library. Includes slides, video, and Jupyter Notebooks. (Targeted at web developers but suitable for a wider audience.) Created by Sarah Bird.
Browser-based application for a number of different programming languages (including Julia, Python, and R) that can be used to facilitate open and reproducible science by combining live code,... more
|Python, R, Julia, MATLAB|
|Materials for the Data Science Services statistical software workshops from the Institute For Quantitative Social Science at Harvard||List||
List of tutorials from workshops hosted by the Institute for Quantitative Social Science at Harvard University
|NU Linguistics Lab Documentation and Tutorials||Tutorial||
Basic tutorials for automating speech signal analysis