FlowingData: A blog that explores how statisticians, designers, data scientists, and others use analysis, visualization, and exploration to understand data and ourselves. Their tutorials are a great resource for learning how to visualize data.
Humanities Data Analysis: practical guide to data-intensive humanities research using the Python programming language.
Data Carpentry: Data Carpentry develops and teaches workshops on the fundamental data skills needed to conduct research. Its target audience is researchers who have little to no prior computational experience, and its lessons are domain specific.
Software Carpentry: Software Carpentry is a volunteer organization whose goal is to make scientists more productive, and their work more reliable, by teaching them basic computing skills. Their lessons are domain specific and cover a range of topics including programming, version control, and data management.
TEI by Example: A tutorial that introduces the Text Encoding Initiative (TEI), walking individuals through the different stages in marking up a document in TEI (Text Encoding Initiative). Besides a general introduction to text encoding, step-by-step tutorial modules provide example-based introductions to eight different aspects of electronic text markup for the humanities.
Machine Learning Glossary: A glossary of machine learning terms and concepts, maintained by Google’s developers.
Natural Language Processing with Python: A book that introduces the field of natural language processing using the Python programming language and the Natural Language Toolkit (NLTK).
#dariahTeach: Platform for Open Educational Resources (OER) for Digital Arts and Humanities educators and students. It is a place for people to publish their teaching material and for others to use it in their own teaching.