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  1. Be able to contribute to debates about the place of data analysis in the humanities from both a technical and theoretical perspective, in a way that lets you responsibly elicit “data” (or as Johanna Drucker would have it, “capta”) out of more humanistic stores of knowledge.

  2. Acquire proficiency in the manipulation, transformation, and graphic presentation of data in the R programming language for use in the context of exploratory data analysis and presentation.

  3. Know the appropriate conditions for using, and be able to use, some of the major machine learning algorithm for data classification, clustering, and dimensionality reduction.

  4. Execute projects creatively deploying and combining these methods in ways that contribute to humanistic understanding.