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Truman’s M.S. in Data Science and Analytic Storytelling trains you to effectively gather and interpret data. You’ll develop the skills necessary to explain your insights through evocative and digestible visualizations to technical and non-technical audiences alike.

A tech-related undergraduate degree is not required to pursue this program.

Why Truman?

Customize projects to your relevant work or interest areas
Tremendous value — high quality at low cost
Personalized attention from expert faculty
A program designed for the working professional

Curriculum

This course introduces students to the world of data science by providing an overview of the discipline and in-depth exposure to the statistical software environment R, as well as common statistical analyses. Upon completion of this course, students will have a solid foundation upon which to build in completing the remainder of the courses that make up the data science certificate program.
An exploration of techniques used to manage and prepare very large data sets, focusing on the tools needed for future classes.
An exploration of techniques used to find patterns in very large data sets, with an emphasis on the statistical structure of the approaches and practical uses of key tools. Recommended: Completion or concurrent enrollment in PDAT 611G – Big Data Management.
This course introduces the theory and practice of machine learning. Statistical learning techniques such as regression, regularization, and principal component analysis are covered. Programming in a popular machine learning language such as R is reviewed. Approaches such as neural networks, support vector machines, unsupervised learning, and reinforcement learning are covered.
This course develops and understanding of theory and skills in constructing a relevant, ethical, and engaging message using data that tells a coherent, persuasive story to relevant audiences of technical experts and non-experts. Upon completion of the course, successful students will understand how traditional ideas of rhetoric are still appropriate today and how to approach turning a dataset into a story.
And introduction to the principles of good design, with application to data visualization. Students will learn about design principles in general through lecture, example, and pen-and-paper practice. Students will then apply these principles in the context of data analysis and dvisual storytelling using appropriate software tools.
This course introduces students to Big Data ethics and security. Topics to be explored include: Big Data ethics and security issues and explore Big Data techniques and methods.
This course serves as the culmination of  the Masters Program in Data Science and Analytic Storytelling. Students, working alone or in a pre-approved group, complete a data science project within their given discipline. It willl involve a substatial written paper as well as an onlin presentation. Repeatable for up to 6 total credit hours.
This course introduces students to the world of data science by providing in-depth exposure to the software environment Python. Upon completion of this course, students will have a solid foundation on data science techniques using Python.
This course serves as the culmination of the data science certificate program. Students, working alone or in a pre-approved group, complete a data science project within their given discipline. The deliverables for this project include a technical paper written in R Markdown that details the project and the steps taken, and an online presentation of the results.
Practical experience using real world data to tell a data-driven story in multiple presentation styles ot a variety of expert and non-expert audiences. Students will explore several datasets of increasing complexity to explore pitfalls and demonstrating increasing facility telling data stories.
Selected topics in data science. may be repeated for up to six credits.

Gallery of Master’s Thesis Topics

Explore the variety of thesis topics undertaken by graduates of our Master of Science in Data Science and Analytic Storytelling program.

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Data Science Program—Academic Calendar

Program starts in spring and fall each year. Eight-week courses offered year-round.

2026-27

Spring First BlockSpring Second BlockSummer Eight-Week
1/6/27-3/2/273/15/27-5/8/276/1/26-7/24/26
Fall First BlockFall Second Block
8/12/26-10/6/2610/12/26-12/12/26

Admission

SPRING

Preferred Deadline – Apply by December 1

FALL

Preferred Deadline – Apply by August 1

Admission Requirements

  • Transcripts must demonstrate:
    • completion of baccalaureate degree from an accredited institution (or international equivalent)
    • 2.5 cumulative GPA*
      *Or demonstrate sufficient professional experience to prepare them for the proposed field of study.
    • completion of STAT 190 – Basic Statistics**
    • completion of CS 170 – Intro to Computer Science**
      **If you need help completing these requirements, please contact gradinfo@truman.edu about fulfilling them as part of the data science graduate program. Students with workplace knowledge of statistics or programming may request a waiver of the prerequisite, please contact gradinfo@truman.edu to begin waiver consideration.
  • GRE scores are optional. No score is required to apply, nor at any point during the program.

International students should note that the Data Science Program at Truman is online, and you will not be issued a student visa to complete this degree.

Regrettably, we are unable to consider applications for fully-online programs by individuals who reside outside of the United States and its territories at this time. International applicants are still encouraged to consider our face-to-face programs located on campus in Kirksville, Missouri.

Tuition

30
credit hours
$588
per credit hour
$17,640
total estimated tuition*

*Total estimated tuition based on 2026-27 academic year. Tuition subject to change.

Financial Aid

Degree-seeking students enrolled in at least six credit hours per semester are eligible for federal financial aid programs. For more information, see Financial Aid Resources for Graduate Studies or contact the Financial Aid Office at (660) 785-4130 or finaid@truman.edu.

Accelerated Program

Data Science Opportunities for Truman Undergraduate Students

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Data Science 4+1 Program

Data Science 4+1 is an accelerated program for Truman undergraduates to pursue the Master of Science in Data Science and Analytic Storytelling.

You can take up to 12 graduate credits as an undergraduate student to get ahead in your coursework, and 6 of those graduate credit hours can be applied to your undergraduate degree.

Schedule a Virtual Visit

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Virtual Visit

Get an inside look at the online learning environment, meet your professors, and get all your questions answered during a virtual visit.

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Data Science at Truman