Jupyter | SSH Training Discovery Toolkit

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Introduction to Digital Humanities	The aim of the course is to introduce digital humanities and to describe various aspects of digital content processing. The practical aims consist of introducing current data sources, annotation, pre-processing methods, software tools for data analysis and visualisation, and evaluation methods. Currently, we identified that students are somewhat aware of digital humanities but it is difficult for them to dive in and, mainly, to anticipate what they should learn for their future research. A more detailed goal of this course is to present some current projects, show the datasets and technologies behind, and encourage students to explore the datasets and use the technologies on data they already know. A high level goal is to set the knowledge of the technologies and available datasets into the research iteration loop (create hypotheses -> design instruments -> collect data -> analyze and evaluate). Taken from: Teaching with CLARIN: https://www.clarin.eu/content/introduction-digital-humanities
Interactive computing	Service based on Jupyter Notebook enables the creation and sharing of documents containing “live” code, equations, visualisations and texts. It allows to write simple programs, numerical simulations, statistical modeling, data visualization and much more.
Core Curriculum	The lessons introduce terms, phrases, and concepts in software development and data science, how to best work with data structures, and use regular expressions in finding and matching data. We introduce the Unix-style command line interface, and teach basic shell navigation, as well as the use of loops and pipes for linking shell commands. We also introduce grep for searching and subsetting data across files. Exercises cover the counting and mining of data. In addition, we cover working with OpenRefine to transform and clean data, and the benefits of working collaboratively via Git/GitHub and using version control to track your work.
SSDS 2018 - Summer School on Data Science Training Materials	Training materials used for the 3rd Int'l Summer School on Data Science (SSDS 2018) Final resource accessible here: https://github.com/SSDS-Croatia/SSDS-2018

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EOSC-Synergy Training Platform	EOSC-Synergy training platform is set of tools for the creation and conduction EOSC related training courses. It facilitates cloud related courses providing tools for interactive computing. The platform is based on the container’s technologies, that allows for combining together in a suitable learning setup for students/training participants.
GESIS Notebooks	Have a Binder-Ready repository? With GESIS Notebooks, turn this repository into a persistent Jupyter environment, allowing you to continue your analysis from anywhere at any time. This service is intended for use by social scientists. You can build and launch all binder-ready projects without logging in. If you want to have more persistent projects, you need to log in.
Library Carpentry	Library Carpentry workshops teach people working in library- and information-related roles how to: Cut through the jargon terms and phrases of software development and data science and apply concepts from these fields in library tasks; Identify and use best practices in data structures; Learn how to programmatically transform and map data from one form to another; Work effectively with researchers, IT, and systems colleagues; Automate repetitive, error prone tasks.
Harvard University: online courses	About 200 online courses dedicated to various disciplines including humanities and social sciences.
Software Carpentry	Teaching basic lab skills for research computing. Lessons and workshops in three core topics: the Unix shell, version control with Git, and a programming language (Python or R).