Learn how to integrate data science into classroom instruction in any field and prepare students to meet the growing demand for data science expertise in the context of ongoing digital transformation of industry and society.

The Graduate Certificate in Data Science Pedagogy is a program that requires a minimum of 12 credit hours and is designed to prepare K-14 instructors to integrate data science into instruction with the overall goal of preparing students to meet the growing demand for data science expertise in the context of ongoing digital transformation of industry: the process by which firms integrate digital technology into every aspect of operations and bring value to customers. To be credentialed to deliver data science instruction at the higher education level, students are required to take a minimum additional of 6 credit hours of course work to be selected by the students and approved by the Data Science Pedagogy Graduate Certificate committee.

Organizations in every industry, including education, that do not embrace digital transform will struggle to survive the fourth industrial revolution with its blurring of boundaries between physical and digital worlds. To remain competitive in this environment, Mississippi businesses require middle-skill and high-skill data science experts. Mississippi's education and workforce development system must meet this growing demand to remain economically competitive. Yet Mississippi's educators, like those in the rest of the nation, lack adequate preparation to infuse data science into their curricula and instruction. To meet this need, the certificate includes coursework with the twofold purpose of (1) helping instructors become literate in the field of data science by understanding the role data science experts play in improving the performance of institutions, organizations, business, and society; and (2) teaching instructors how to teach the practice of data science in their own classrooms, regardless of subject.

The Graduate Certificate in Data Science Pedagogy is a program that requires a minimum of 12 credit hours and is designed to prepare K-14 instructors to integrate data science into instruction with the overall goal of preparing students to meet the growing demand for data science expertise in the context of ongoing digital transformation of industry: the process by which firms integrate digital technology into every aspect of operations and bring value to customers. To be credentialed to deliver data science instruction at the higher education level, students are required to take a minimum additional of 6 credit hours of course work to be selected by the students and approved by the Data Science Pedagogy Graduate Certificate committee.

Students who complete the Graduate Certificate in Data Science Pedagogy will be able to:

  • Define data science as a field of inquiry and an industry sector.
  • Outline the role of data science in the context of digital transformation of institutions, organizations, businesses, and society.
  • Outline data science methods and practices in the context of the entire data lifecycle including the production, acquisition, storage, and use of data to solve human problems.
  • Apply and integrate principles of data science into classroom instruction.

Program Structure

Course Code Course Name Credit Hours
DSCI 8013 Data Science Literacy Pedagogy 1: Governance, Ethics, and Data Science Applications 3
DSCI 8023 Data Science Literacy Pedagogy 2: Technical Overview of Data Science Methods and Strategies 3
DSCI 8033 Data Science Classroom Integration 3
CSE 8423 Data Science: Concepts and Practice 3
  Total Hours 12

Admissions Process

Graduate Admissions

Applications for the degree programs are reviewed three times a year. The application deadlines for those semesters are as follows:

  • Fall Semester – August 1
  • Spring Semester – December 1
  • Summer Semester – May 15
    1. Submit an online application. You will choose Data Science Pedagogy as your program of interest and Online Education as your campus.
    2. One official transcript showing bachelor’s degree or progress toward degree. (For international students, please submit a copy in native language along with translated copies, if appropriate.)
    3. One official transcript showing ALL work after bachelor’s degree. (For international students, please submit a copy in native language along with translated copies, if appropriate.)
      • Electronic transcripts should be sent to: gradapps@grad.msstate.edu Mississippi State University, Graduate School. Only one copy of an electronic transcript is required.
      • Paper Transcripts Address (USPS):
        Mississippi State University
        The Office of the Graduate School
        P.O. Box G
        Mississippi State, MS 39762
      • Physical Street Address (for DHL, Fed Ex, UPS, DHS, etc.):
        Mississippi State University
        The Office of the Graduate School
        175 President Circle
        116 Allen Hall
        Mississippi State, MS 39762
    4. Pay $60 non-refundable application processing fee

PLEASE NOTE

In general, students who are not admitted into a degree program are not eligible for student financial aid funds. For more information please visit Student Financial Aid to see if you will be eligible or not while taking courses for the Data Science Pedagogy.

Courses

DSCI 8013 Data Science Literacy Pedagogy 1: Governance, Ethics, and Data Science Applications
General subject-matter introduction to the field of data science and data science instruction with a focus on governance, ethics, and data science applications in many fields.

DSCI 8023 Data Science Literacy Pedagogy 2: Technical Overview of Data Science Methods and Strategies
General subject-matter introduction to the field of data science and data science instruction with a focus on data science methods and practices.

DSCI 8033 Data Science Classroom Integration
Applying and integrating principles of data science into the context of the classroom. Topics include importance of data science across the domain; digital citizenship; career exploration; and an historical perspective on analyzing, posing, and solving problems using data.

CSE 8423 Data Science: Concepts and Practice
This course introduces the fundamental concepts of data science, covering data representation and transformation, visual data analysis, statistical modeling, tidy and relational data, functional data-flow programming, and communicating results. The course introduces the practice of data science, using standard data science tools and languages.

Academic Advising

After gaining admission to the university, you must contact your assigned advisor to determine the courses most appropriate to take. Before the upcoming semester, your advisor will send an email to your MSU email account, making course recommendations based on your program of study.

Mississippi State University uses email as its official means of communication with all MSU students. Please check your MSU email account (NetID@msstate.edu) daily. Information on setting up your MSU email can be found at the link for student services.

Headshot of Taylor

Lynn Taylor

Data Science

    • Academic Coordinator
662-325-3168

Contact Information

Headshot of Taylor

Lynn Taylor

Data Science

  • Academic Coordinator
662-325-3168
Headshot of Mark Jimmerson

Mark Jimerson

Online Education

  • Coordinator
662-325-2655