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LEARNING
learning

LEARNING

COMMUNITY

  • Coding and Data Science for the Humanities.{:target="_blank"} Fall 2020 and Spring 2021. Highly accessible, humanities-oriented presentations, including DIY tutorials (see "DIY Tutorials," below) and critical reflection on theoretical issues and implications. A special series of the Data Science Colloquium, which is a project of the Data Science Across the College initiative, directed by Mark Turner and Timothy Beal, in collaboration with h.lab{:target="_blank"}, Red Hen Lab{:target="_blank"}, and AI.Iliff{:target="_blank"}. All presentations will be live recorded Zoom sessions. Ask [email protected] for an invitation.

    "Getting Started with Coding for Humanities Scholars," by Micah Saxton, Tufts University, and Michael Hemenway, AI.Iliff, October 28, 2020 @ 3pm ET. Video recording here and accompanying Google Colab notebook here.

    "Build a Bot: A DIY Toy that Makes You Think," by Timothy Beal, Department of Religious Studies, with Michael Hemenway, AI.Iliff, November 4, 2020 @ 3pm ET

    "Transformers: Analyzing Language with Deep Learning," by Justin Barber and Michael Hemenway, AI.Iliff, November 18, 2020 @ 3pm ET

    "Data Science in Art: Discerning the Painter's Hand," by Elizabeth Bolman, Department of Art History and Art, and Ina Martin, Michael Hinczewski, and Kenneth Singer, Department of Physics, December 9, 2020 @ 3:00 pm ET

    "Introduction to the Red Hen Lab Rapid Annotator," by Peter Uhrig, February 10, 2021 @ 3pm ET

    "Data Science for FrameNet and Frame Blends," by Wenyue Xi and Mark Turner, February 24, 2021 @ 3pm ET

    "Fine-grained Semantic Representations for Multimodal Data Analysis," by Tiago Torrent, Federal University of Juiz de Fora – FrameNet Brasil, March 10, 2021 @ 3pm ET

    "Corpus-Based Genre Analysis in Writing Research and Pedagogy," by J. Elliott Casal, Research Scholar, Department of Cognitive Science, Case Western Reserve University, March 24, 2021 @ 3pm ET

    "Machine Learning for Poetic Creativity in Oral Traditional Performance," by Cristóbal Pagán Cánovas, Ramón y Cajal Assistant Research Professor, Department of English Philology, University of Murcia; Alexander von Humboldt Fellow, Quantitative Linguistics, University of Tübingen, April 14, 2021 @ 3pm ET

  • Data Science Colloquium.{:target="_blank"} Spring 2020. A project of the Data Science Across the College initiative, directed by Mark Turner and Timothy Beal and supported by a grant from former CWRU President Barbara Snyder, to build on strengths and potentials across many fields, including the arts and humanities, social and behavioral sciences, and natural and mathematical sciences, to elevate data science and machine learning as a college-wide focus for research, scholarship, and curriculum development. All presentations available as Zoom recordings.

DIY TUTORIALS

  • Build a Bot.{:target="_blank"} A Colab notebook created by Timothy Beal with easy-to-follow directions to build your own fully functional text bot. Based on the code for the KJVBot{:target="_blank"} tweeter, it auto-generates its own verses based on the King James Version Bible. It is easily adaptable to other texts. No coding experience is necessary here, but each step is annotated for those who want to understand more about what's going on from line to line.

  • Getting Started with Coding for Humanities Scholars{:target="_blank"} Aa highly accessible, humanities-oriented, hands-on introduction to coding and natural language processing (NLP) in the programming language of Python. A great place to take your first steps into coding for the humanities! Created by Micah Saxton and Michael Hemenway. See also this video presentation of the notebook by Micah and Michael.

COURSES

  • Coding for the Humanities: Python, Natural Language Processing, and Machine Learning (HUMN 305/405).{:target="_blank"} New for Spring 2021 at CWRU! An entry-level, humanities-oriented introduction to coding, natural language processing (NLP), and machine learning for undergraduate and graduate students. Course objectives include: (1) hands-on mastery of fundamental coding skills in Python (a powerful and highly readable programming language that is the lingua franca of NLP and machine learning); (2) individual and collaborative lab projects that develop skills in problem-solving and program design; and (3) sustained critical reflection from humanities perspectives about the tools and processes with which we are experimenting. The course will be of value for students who are developing and designing research projects as well as for those entering professional contexts in which basic coding skills are advantageous.
          Appropriate to its content, this is a hybrid course, combining asynchronous individual and collaborative work online with on-site sessions to share work in progress and facilitate critical reflection and theorizing about that work. Evaluation based on mastery of basic Python, an individual coding project, and a collaborative group coding project.

OTHER RECOMMENDED RESOURCES

  • Python for Everybody.{:target="_blank"} Dr. Charles Severance’s outstanding, free series of courses for learning Python and data visualization. Includes clear and helpful videos, exercises, and quizzes. No experience necessary!

  • The Programming Historian.{:target="_blank"} "We publish novice-friendly, peer-reviewed tutorials that help humanists learn a wide range of digital tools, techniques, and workflows to facilitate research and teaching."

 

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