Data: it's the language of our digital age and an integral part of all academic disciplines. We are poised to augment subject-specific teaching with our broad data science expertise, providing an edge in our data-driven world.

Course Support

Session Planning and Instruction

Engage with our team for a single instruction session or embed us into your classroom and we'll support course content all semester. Data workshops help students find, evaluate, analyze, and visualize data to support their learning.

Request an Instruction Session.

Group Project Support

We extend our support to group projects teams, such as Data Analytics Project Lab (ENGM 204), where we lend our data expertise to strengthen project outcomes.

Add Us to Your Group Project.

Individual Consultations

Our team is available for one-on-on meetings for a personalized understanding of data, computational methods, and support for your research. We work with everyone in the Dartmouth community.

Schedule a Consultation.

Workshops

Our workshops are designed to meet a wide array of interests that cross disciplinary boundaries.

Domain-Specific Bootcamps:

Immersive learning experiences in specific domains, like the Data Analytics in R Bootcamp. We work with groups or departments to develop individualized content and reusable materials to take your computational workflows to the next level.

Audience-Specific Workshops:

Sessions targeted to specific audiences, ranging from undergraduate researchers to faculty.  We tailor workshops to meet your needs and can teach the full-spectrum of research data management, data science, machine learning, generative AI, data literacy, and computational scholarship skills.

General Workshops:

Work with us to build a custom-tailored workshop from many proven, open-source lessons. Past and ongoing workshops include

  • Reproducible Research in partnership with Research Computing
  • Carpentries Workshops: R for Reproducible Scientific Analysis, Plotting and Programming in Python, The Unix Shell,  and Version Control with Git

Upcoming Events

April 30
Reproducible Research
Getting Started with R and R Studio 1:00pm - 2:00pm Event Details
May 02
Reproducible Research
Building Datasets (Corpora) 3: Construct and Analyze a Full-Text Corpus with Constellate 12:00pm - 1:00pm Event Details
May 02
Reproducible Research
Beginning Collaboration with Git 2:00pm - 3:30pm Event Details

Data Specific Resources

When it comes to learning resources, we believe in sharing our knowledge openly and transparently. We use the following platforms to provide a wealth of educational materials:

Jupyter Hub

An interactive computational environment where we share live code, equations, visualizations, and narrative text. Our notebooks on Jupyter Hub allow students and researchers to reproduce and experiment with our lessons, reinforcing their learning and enabling a more immersive understanding of data science concepts.

View our Notebooks on Jupyter Hub

GitLab

All our teaching materials, including course outlines, scripts, datasets, and codes, are stored in GitLab. This enables easy version control and collaborative development. These resources are at your fingertips whenever you need to revisit a lesson, practice a technique, or collaborate on a project.

Visit our GitLab Repository

Videos of Recorded Sessions

For those who prefer visual learning or want to revisit a lecture, we can record and store our workshop and seminar sessions. These recorded videos can be accessed at your convenience to ensure you never miss out on any of our teachings.

Through these repositories, we provide open, easily accessible, and highly reproducible materials, facilitating learning at your own pace and convenience.

Email & Phone

Research Data Services

Address

Research Data Services

Berry Library
Rooms 365-366
HB 6025
Hanover, NH 03755

Our Staff

Jeremy Mikecz at Vitcos, Peru
Jeremy M. Mikecz
Research Data Science Specialist
green circle with person icon on blue grid
Lora C. Leligdon
Head of Research Data Services
Simon Stone photo
Simon Stone
Research Data Science Specialist
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