• What the term “digital humanities” means in different disciplines.
• How common digital tools work and examples of projects using them.
• How various file types can be used to create, gather, and organize data.
• How to use command-line functions to analyze text.
• How to use free tools to create visual text analysis.

Lesson 1: Digital Humanities and Data

• Explain the term "digital humanities," and how it is understood across humanities disciplines.
• Describe the research journey as a partnership between researcher and library collections and staff.
• List examples of the limits of classification.
• Describe the implicit and explicit hierarchies that are created when gathering and analyzing data.
• Distinguish between what counts as data and what does not.
• Identify different data formats and how they fit into a research workflow.

Lesson 2: Digital Humanities Projects and Tools

• List tools of data analysis that can be applied to text in any language, space, networks, images, and statistical analysis.
• Evaluate existing digital platforms based on features that can be used for data analysis within different fields such as literature, history, art, and music.

Lesson 3: Acquiring, Cleaning, and Creating Data

• Identify the differences between unstructured, semi-structured, and structured data.
• Distinguish between different file types, their definitions, and applications.
• Apply intellectual property rights to the downloading and sharing of data.
• Practice different ways of downloading or creating data.

Lesson 4: The Command Line

• Understand how command line functions work.
• Apply command line functions to text files.
• Create smaller text files from larger files using command line prompts.

Lesson 5: Working with Tools - Voyant

• Create data from multiple text files using Voyant.
• Compare data results across text files using visualizationin Voyant.