Translational Data AnalyticsMaster of Translational Data Analytics – Online

About us

Become an expert in data storytelling with the fully online Master of Translational Data Analytics from Ohio State's Translational Data Analytics Institute. This truly interdisciplinary program is designed for working professionals in fields as diverse as health care, education, finance, government, and the arts who want to apply statistics, machine learning, and user experience and data visualization tactics to uncover and present insights from data.

Subject matter experts from the departments of Computer Science and Engineering, Statistics, Design, and the Advanced Computing Center for the Arts and Design engage students in practical and experiential learning projects. Through a design thinking lens, students can immediately apply new research methods and in-demand data analysis skills with a focus on developing full-cycle workflows for big data.

Unique in the growing data science landscape, no significant background in analytics and programming is required, and students have the flexibility to take their courses in an asynchronous or synchronous format or a hybrid of the two. Each cohort is carefully curated, placing an emphasis on students' varied backgrounds and disciplines to enrich team-based case studies and projects. Students will spend the final two semesters of the 33-credit program working on diverse teams to complete a workforce-focused capstone project.

Beginning Fall 2021, students will be able to select one of two cohort pathways, either a 5-semester or 10-semester option, at the time of application. Read about our curriculum, each pathway option (5 or 10 semesters) and the content of our courses online (including our syllabi) at: https://tdai.osu.edu/education/masters-translational-data-analytics.

Here are the basics about what we teach:

  1. The core concepts of statistical analysis,

  2. The foundations of big data computing, data mining and machine learning

  3. Information design, the foundations of data visualization and emerging trends in data storytelling

  4. How to assemble and present compelling user experiences and user interfaces

  5. Three skills focused seminars in data governance, research methods and in-demand "soft" professional skills

  6. Appication of your learning in real-world capstones